In a prior post I spoke to the importance in getting involved in various organizations and groups as a way to build skills, expand one's network, and give back. Volunteering around causes you care about is vital to so many areas of one's life. Sadly, however, volunteer engagement is on the decline. 

In a survey of over 1,200 non-profit leaders conducted in 2022, 46.8% said that recruiting sufficient volunteers is a big problem for their organization. Those numbers have almost doubled from the 2003 survey, in which 29% of nonprofits saw this issue as a big problem. Furthermore, nearly half of non-profit leaders believe that the lack of volunteers is a "big problem" to their organizations fulfilling their missions. This same report also pointed out that the ~100 institutional funders they surveyed were less likely endorse the belief that volunteers provide important programmatic and functional support to non-profit organizations (when compared to responses from non-profit leaders) and  were less aware of some of the challenges organizations faced in recruiting volunteers. This gap in funders' understanding of volunteer engagement and impact may result in it being difficult for non-profits to solicit funding support for these efforts. Importantly, the study also found that most non-profit organizations do not ask for funding for volunteer engagement and emphasized that funders see benefits to supporting volunteer engagement if they perceive the investment increases the capacity of volunteers to form or strengthen connections with other people or organizations in the community.   

I have seen some of the challenges in volunteer recruitment and engagement first-hand as part of my involvement in two organizations close to my heart: the National Postdoctoral Association (NPA) and the Graduate Career Consortium (GCC). Across both organizations, interest and engagement with one might call "service" committees has eroded, potentially because some volunteer tasks and activities in these areas seem like "work". 

While the NPA has a small staff (of 3.5 FTE as of this writing), many of them are focused on the day-to-day running of the organization and trying to "keep the lights on." As such, focusing on a complex problem like "volunteer engagement" and "leadership development" is a challenge. The GCC suffers from the fact that is a 100% volunteer-run organization. So, all day-to-day operational tasks of the GCC lies it its leaders and members to execute. Having served on the Executive Committee of the GCC, I can tell  you that it is A LOT of work. Furthermore, much like the NPA, GCC leadership spends much of its time trying to keep the organization running and fiscally stable.  

Both the NPA and GCC are great organizations with important missions and are working diligently to try to improve and evolve their operations and structures to serve their members better. That said, they can only do so much at their current volunteer levels. Both organizations would be transformed if more members engaged in volunteer efforts and activities. This requires infrastructure and a plan to accomplish, however. And while leadership in each organization can start to shape processes and procedures to improve volunteer recruitment, engagement, and retention, it will ultimately be up to volunteer leaders across various committees and taskforces within each organization to do the work. We need to engage volunteers in volunteer engagement which highlights the weird circularity of the problem. It will take effort to get this fly wheel going but perhaps combining established volunteers and leaders in each organization with newer volunteers would allow for fresh ideas and insights to emerge. There are no easy answers but we have to start somewhere. 

Certainly the COVID-19 pandemic hit many hard and led to burnout and a re-setting of priorities. Ironically, non-profit, volunteer-drive organizations offer an important service to those affected by the pandemic. Feeling isolated and uncertain? Organizations that foster community, connection, and resource sharing conceptually are more important to you now. But taking advantage of organizational resources and programs is quite different from helping to run and manage them. 

Perhaps part of the lower levels of engagement in volunteer work (and paid work, too) is a general issue in our limited attention and bandwidth today...stretched to its breaking point with the proliferation of content and technologies engineered to distract us. Email, notifications on applications like Slack, and the infinitely vast distractions available via the internet and streaming content services like Netflix provide a countervailing force on our attention and focus on work that is almost insurmountable. And this is work we are paid to do that gets crowded out by digital distractions. What hope do we have for engaging in work we are not paid to do (ie, volunteer work) in such an environment? 

There is also the issue that engaging in volunteer or leadership capacity in a non-profit organization is WORK. It requires effort and commitment that many have too little of these days. 

Similarly, developing more robust structures to engage and support volunteers within non-profits requires work on the part of an organization whose bandwidth is already stretched due to lower levels of engagement. Ironically, solving the problem often requires more engagement and volunteers. One can see how this state of affairs could lead to a sort of "doom loop" where a decrease in volunteer engagement erodes the organization's ability to "get stuff done" and provide examples of projects and activities for prospective volunteers to get excited about, ultimately leading to less new volunteer interest in the organization. 

There is some interesting research looking at what factors affect both volunteer retention and engagement. In the sample of 232 active volunteers working in social or environmental non-profit organizations, regression analyses found that commitment, and not engagement, predicts intention to remain with the organization, and that engagement, and not commitment, predicts psychological well-being of the volunteers. These data suggest a need for non-profits to articulate their "why" to volunteers to solidify their commitment to the organization and its mission to keep them engaged and then through their engagement, volunteers improve their sense of well-being (ie, feel "good" about their involvement). 

Indeed, other studies show that the volunteers perceive that their satisfaction with life had significantly changed as a result of doing voluntary work. In addition, this study found that the link between self-determined types of motivation and eudaimonic well-being ("living a life of virtue in pursuit of human excellence") is mediated by engagement. Engagement also mediated the positive effects of motivation on satisfaction with volunteering, which in turn acted as a second-order mediator on the relationship between self-determined types of motivation and hedonic well-being ("feel good"). In other words, volunteers need to be internally motivated to contribute to an organization and then be given pathways to engage with the organization to feel fulfillment from their involvement on a variety of levels. 

Qualitative analyses of interviews with experienced volunteer managers have found that key engagement strategies could include "fulfilling ulterior motives" of the volunteers. So, organizations must work to understand what is motivating their volunteers to engage and how can the organization help to fulfill this need while also involving the volunteer in activities crucial to the organization itself. Flexibility in engaging volunteers also came up this analysis, supporting the notion that providing volunteers different mechanisms for engagement (including potentially asynchronous tasks) allows them to remain engaged on their own terms. None of these findings are that surprising but they emphasize a need for organizations to develop infrastructure to hear from their prospective volunteers and offer them a variety of options to engage with the organization. Additional studies on volunteer engagement are linked at the end of this article. 

Reader, perhaps you can help jump-start volunteer engagement efforts in societies or organizations you care about by taking the first step of getting more involved? This could look differently for each person and organization but active engagement of some kind is critical. Perhaps you can identify a leader of a subcommittee or group within an organization and setup a meeting to learn more about their work and whether your skills and interests could contribute in some way? These conversations (and your continued involvement in an organization) ultimately help you widen and broaden your professional network and you can develop new skills in interpersonal communication, project management, and leadership by becoming involved in a project or initiative within the organization. If you are helpful and provide value, people around you will notice and could also be excellent references for jobs you may apply to in the future. In closing, volunteering is helpful for you professionally but also helps the organization accomplish its mission. It is the ultimate win-win. So, what are you waiting for? 

If you are a postdoctoral scholar or individual working to support this population, consider joining the NPA as a volunteer. There are several committees and taskforces to get involved in. 

If you work in the graduate-level (graduate student or postdoc) career & professional development space, the GCC is an amazing organization that could benefit from your contributions and involvement. Learn more about GCC committees and the organization's work and consider joining as a member if you aren't one. 

Additional Reading & Resources

• Nonprofit Volunteer Management: Three Tips to Increase and Maintain Engagement
• Initiative for Strategic Volunteer Engagement
• Council for Certification in Volunteer Administration 
• University of Maryland Do Good Institute
• Understanding and Improving Employee Engagement - Insights from Gallup

Research on Volunteer Engagement​

• Volunteer engagement and organizational commitment in nonprofit organizations: What makes volunteers remain within organizations and feel happy?
• Enhancing Volunteer Engagement to Achieve Desirable Outcomes: What Can Non-profit Employers Do?
• Volunteer Engagement and Retention: Their Relationship to Community Service Self-Efficacy
• Leading Volunteer Motivation: How Leader Behaviour can Trigger and Fulfil Volunteers’ Motivations

Get Involved!

• Great Nonprofits.org
• Volunteer Match

More from the Blog

• Why You Should Get Involved in Things Outside the Lab/Work
• ​To Be Rather Than To Seem

Life is not a zero-sum game.

In 21st Century American society it is easy to get sucked into the mindset of "us against them" or "me against the world" that appeal so much to our basal instincts, including fear of others. Human's penchant for being alert to threat and risk is deeply embedded in our evolution and requires cognitive effort to resist. Additionally, inequality and the precariousness of making a living in modern, capitalistic America leads to many living on the edge and/or fearful of falling from their current economic position.

​This pessimistic economic mindset and mood has negative spillover effects on society. Studies show that increases in economic inequality are associated with political polarization in the Unites States (US) and globally. An adversarial mindset to "the competition" both individually and collectively (ie, "zero-sum thinking") can thus drive both economic and political actions that are harmful to society as a whole. ​

What is "zero-sum thinking"? Essentially it is the belief that benefits to one person or group tend to come at the expense or cost of other persons or groups. The concept is thought to originate from work by the anthropologist George M. Foster who investigated "peasant" societies' view of the world and came to the conclusion that many individuals in these societies have an “Image of Limited Good.” That is to say, many people see all of the desired things in life (food, property, wealth) as existing in finite quantity and limited supply. 

A fascinating paper by Chinoy et al from 2022 found, among other things, specific factors that were related to more or less zero-sum thinking in a survey of 15,000 individuals in the United States. Specifically, they found respondents view the world as less zero-sum if:

• They, their parents, and their grandparents experienced more upward mobility during their lifetimes.
• They, their parents, or their grandparents immigrated to the United States.

While zero-sum thinking is commonly felt and believed, a further investigation into just what this doctrine proports leaves one feeling a different approach is not only needed but warranted. When others win, you can win. A modern nation relies on taxes from its citizens (and immigrants - to the tune of $467.5 Billion in federal and state/local taxes 2019) to fund projects and priorities that benefit others. What becomes tricky to negotiate is who is being taxed and who benefits from the government's actions and interventions. I would argue we all benefit at the most basic level as a growing tax base ultimately leads to more robust services and programs. ​

Despite the fact that the US Federal Government provides useful benefits to its citizens (Social Security, rule of law, security), the "rugged individualism" that is so pervasive in American culture leaves many to feel they have to "got it alone", that the government is not their friend, and that "others" are the competition. In truth, no one succeeds alone.  ​

Ironically, perhaps the most outward manifestation of the combination of American Capitalism and individualism is the reverence for the entrepreneur. The lore of the Silicon Valley start-up that grew from a garage to a global behemoth is seductive if not often the full story. Entrepreneurship is most often predicated on having a sufficient "cushion" of support including family wealth (among other factors) or a partner who is working in a more "stable" position with provided employer-sponsored health insurance, for instance. In some ways, pursuing entrepreneurship in America seems to be privilege inaccessible to many. Perhaps not surprisingly, then, some studies have found a positive relationship between inequality and entrepreneurship across US states, though the relationship between entrepreneurship and measures of a country's overall economic health are nuanced (economies as a whole can benefit from entrepreneurship even if all individuals don't). 

In essence, many American entrepreneurs have in place their own "safety net" to ensure that they can take risks in starting something new and bringing new ideas and products to market. What might be possible for entrepreneurship and innovation in the US, though, if more people were given a sufficient social safety net?

Entrepreneurship is a risky endeavor. One is taking the chance on advancing a new idea, solution, or product that faces a variety of hurdles to success. Some of these hurdles include entrenched interests and firms who seek to maintain market dominance while other challenges include communicating the value of the new idea to potential investors, partners, and ultimately customers. ​

On top of the myriad logistical challenges of entrepreneurship, systems of social support within the United States in particular make striking out on one's own a major challenge. For example, health insurance in the US is often tied to employment and while expansion of health insurance options through government initiatives like healthcare.gov are helpful, the costs of many of the government-backed health insurance offerings are prohibitive. This is perhaps the most salient example of how the robustness of a "social safety net" can affect one's willingness to engage in entrepreneurial activities, which has been demonstrated to be the case in prior work. There are a variety of social safety net programs beyond affordable health insurance that can matter including some form of universal basic income to provide a floor of economic stability and/or childcare subsidies to limit an expensive cost barrier to millions of parents participating fully in the economy. One can imagine more robust government initiatives to lower healthcare and childcare costs alone could make an entrepreneurial path more attainable. ​

There are also arguments that redistribution through the provision of public goods may help reduce both inequality and political partisanship/polarization. These initiatives help individuals, our communities, and our society function better. ​

The injection of stimulus checks to US households during the COVID-19 pandemic provided a mini experiment in the effect of income stabilization on entrepreneurship. We saw an increase in small business formation within the US during this time and while correlation does not prove causation, many speculate increased government stimulus was a key driver of this behavior. 

Regardless of the exact causes for the spike in new businesses, these trends are quite different than prior years where entrepreneurship was on the decline. And while entrepreneurship in the US is climbing post-pandemic, it remains uncertain whether the new businesses formed will result in an increase in employment (ie, businesses that ultimately hire employees to grow).​

It is often the case that for a new business to grow and expand it must be in some way innovative, bringing new products and solutions to market. And innovation at a macro level is critical to the growth and development of large economies. So, where does innovation stand today? 

Recent data suggests declines in US innovation over the past several decades. A January 2023 paper published in the journal Nature found that from 1945 to 2010 scientific papers and patents are increasingly less likely to break with the past in ways that push science and technology in new directions. While some work suggests the key measure in the aforementioned Nature paper, the disruption index, may be biased by citation inflation or a growth in publication rates, the study prompted many to ask if our current systems and incentives are hindering true scientific innovation. 

There is a twisted irony to the fact that a concentration of resources and power in a hyper capitalist "winner take all" system ultimately can stifle innovation and progress. Established power players (think big technology companies in the US) become entrenched and work hard to maintain their market dominance. 

The concentration of resources also occurs in various societal structures and working environments. Even those institutions deemed a societal good can succumb to market forces. Higher education, especially in the United States, is an interesting example where there truly are "elite" institutions whose resources dwarf others, leading to higher levels of research productivity (through graduate student and postdoctoral research labor advantages) and placement of their alumni into faculty positions. Cumulative advantage takes hold, ensuring those considered the "winners" in their spaces continue to win. 

We must ask if all this concentration is good for our society as a whole, especially as innovation drives economic growth. ​A paper by Nicholas Bloom and colleagues (Are Ideas Getting Harder to Find?) posits that economic growth arises from people creating ideas and can be captured by the product of research productivity x number researchers. Their paper finds that while research effort has risen substantially over the past few decades, research productivity is declining sharply. 

How might we advance research and innovation further? A more thoughtful distribution of resources to ensure funding is not overly concentrated would help. Furthermore, increasing access to opportunity will help bring diverse perspectives, skills, and ideas to the table.
​And so we come to the importance of improving immigration to the US to help in these areas. 

The US is a nation of immigrants and data show embracing more accessible immigration practices can assist us as our current population ages and in the process help grow our economy. In addition, immigrants drive American research and innovation, making our economy more dynamic. An important study released in December 2022 found that while immigrants represent 16% of all US inventors, they produce 23% of total innovation output (which was measured by number of patents, patent citations, and the economic value of their patents). The study also found that immigrant and native-born collaborations drive additional innovation through the mixing of ideas and perspectives. 

Another study released in 2022 has shown immigrant entrepreneurs play a large role in founding or co-founding successful US companies. Specifically, over half (55%) of America's start-up companies valued at $1 billion or more had at least one immigrant founder. That percentage rises to 64% if founders or co-founders who are the children of immigrants are included. ​

What is amazing about the impact of immigrants on US innovation is how difficult it is for many highly skilled individuals to successfully work in the US. Current caps on H-1B employment visas for the private sector and various backlogs in the review of applications for green cards makes the recruitment and retention of foreign talent to the US challenging. ​

And while fears of immigrants taking US Citizens' jobs and opportunities are certainly understandable, they are often unwarranted based on the data. 

Importantly, data show an increase in H-1B science, technology, engineering and math (ie, STEM) workers in cities is associated with significant gains in wages for natives. A recent study, published in March 2023, found evidence that large multinational companies based in the US were likely to replace skilled visa rejected employment with "offshoring," ie, employing a skilled worker outside the US, implying that US companies cannot necessarily get talent from current citizens in all cases.

The evidence that H-1B employment is not detrimental for native employees is somewhat conflicting, however. An October 2022 study looking at US firms who "won" versus "lost" the H-1B visa lottery (ie, were able to obtain H-1B visas for skilled, immigrant employees, or not) found some evidence that additional H-1B employees "crowd out" other workers at the firm. Furthermore, this study found some evidence that additional H-1Bs increase firm profits and decrease payroll costs per employee. From a purely economic point of view, one could argue that these data are supportive that the H-1B program improves firm profits even if it potentially hurts the employment prospects of some native employees. 

The Economic Innovation Group, a bipartisan public policy organization, has published important data on the topic of immigration and innovation, among others. They also surveyed the American voting public in 2022 on their perspectives on skilled immigration in the United States. They find that most US voters do not have strong opinions on the economic impact of immigration on the country or are split in its effects being economically net positive (38%) or negative (37%), despite evidence that skilled immigrants boost a variety of economic metrics. When the survey administrators better gauged support for specific skilled immigration programs that would boost the US economy and innovation, support was over 70% overall and over 60% in registered Republicans, who are politically more likely to oppose immigration. Thus, there are signs that immigration reform can be a winning political position, especially if it is framed as an economic and innovative "win" for the country. 

In closing, to grow entrepreneurship and innovation in the United States we need to make opportunity more inclusive to our citizens and support more effective immigration pathways for skilled workers. We need to have an abundance agenda - more social safety nets, more community support, more inclusion, and more access to education, opportunity, and employment in America. 

Scott Galloway echoes this abundance notion in a piece on greater accessibility to higher education. Knowledge itself should not be a scarce and expensive resource to obtain. Increasingly, with the proliferation of data and content on the internet, finding information is easy even if extracting knowledge is not. One could even make the argument that it is precisely due to the overwhelming amount of information available online that finding true knowledge has become more difficult. Our higher education institutions have a role to play in helping turn data and information into knowledge and producing individuals with the necessary skills and values to grow our economy responsibly. The US is in a unique position to provide opportunities and freedom of thought and expression to our citizens and future citizens (ie, immigrants), which allows them to innovate and make the world a better place. Higher education is and can remain our "front door" to the some of the best and brightest young minds who come to America to learn, live, and prosper, while positively impacting our economy. But we can't take international students and scholars for granted. 

In order for the United States to reach the ideals expressed in our founding - "life, liberty, and the pursuit of happiness" from the Declaration of Independence - we must recommit to being a welcoming nation. Expanding immigration pathways for highly skilled workers who want to live and work in the US and contribute to our economy while advancing their own well being should be a win-win for these individuals and our country. We must get past our zero-sum thinking and remind ourselves that in a truly inclusive and democratic society, when our neighbors are allowed the freedom and opportunity to leverage their skills and expertise to their economic benefit, our economy as a whole becomes more robust and we all prosper. 

To innovate, people must be allowed to think, speak, publish, associate, and disagree.
They must be allowed to save, invest, trade, and profit. In a word, they must be free.
- From ​Superabundance 

The diversity of our nation presents challenges and opportunities. As a nation of immigrants, cultures and beliefs collide and mix here like almost no where else on Earth. ​

The American entrepreneurial spirit, commitment to capitalism (greed is good?), and our "rugged individualism" are all assets and, sometimes, liabilities. How we leverage and refine our current systems and beliefs will ultimately determine whether our future is bright or diminished. Through caring and compassion for our current citizens and those who want to join us (immigrants) I think we can achieve a more prosperous future for all of us.   

The National Science Foundation (NSF) in the United States collects two surveys of doctorate recipients that seek to better illuminate and understand Ph.D. career pathways.

• The Survey of Earned Doctorates (SED) is an annual census conducted since 1957 of all individuals receiving a research doctorate from an accredited U.S. institution in a given academic year. The 2021 SED data was released in October 2022 and is currently the most up-to-date data available. Data from the 2022 SED will be released in October 2023.
• The Survey of Doctorate Recipients (SDR) provides demographic, education, and career history information from individuals with a U.S. research doctoral degree in a science, engineering, or health field. It seeks to capture a snapshot of the doctoral workforce by surveying PhD holders across a range of ages and is administered every two years. The 2021 SDR data was released in January 2023. New SDR data will be collected in 2023 and reported in 2025 most likely. 
  

Given the popularity of my previous blog posts examining the 2019 SDR and 2019 SED data, I thought revisiting these surveys and sharing the most up-to-date insights from them would be helpful to graduate students, postdocs, and those who support them. The data give us a good snapshot of the scientific workforce, hiring trends, and salary data for recent Ph.D.s and more experienced individuals holding a doctoral degree. 

The SED asks recent doctorate recipients each year if they have "post-graduation commitments", which could include employment being secured or a postdoctoral position arranged. We can look at this data by the field of doctorate and over time to observe trends in post-graduation commitments. I pulled data from the past 25 years of the SED (from the 1997 to 2021 data) and plotted the trends in post-graduation commitments by field, below.

These data reveal some interesting patterns. First, and perhaps not surprisingly, the humanities and arts fields have lower post-graduation or postdoc commitments than engineering, science, or the education fields. Math and computer sciences have historically seen the highest level of post-graduation commitments. The average percentage of PhD recipients with post-graduation commitments in 2021 was 70%, unchanged from 2020 data. The yearly low point for this percentage across the 25 years analyzed was in 2014 when across all fields the post-graduation commitment rate was 61.4%. 
​
If we zoom into the past 5 years of SED data we see that for many fields, the percentage of recent Ph.D.s with post-graduation or postdoc commitments has increased from 2017 to 2020 and continued to do so from 2020 to 2021, specifically in the life sciences and physical & earth sciences.

In fact, from 2020 to 2021, the percentage of life science doctorates with definite post-graduation commitments increased by 4.8% while the percentage increase was 2.0% year-over-year for the physical and earth sciences. Other fields showed modest decreases of -1% or -2% in post-graduation commitments from 2020 to 2021. 
​
What I find interesting in these data is there is virtually no sign of the COVID-19 pandemic (that began in Spring 2020 and lasted well into 2021) impacting these numbers. It will be interesting to see the 2022 SED data when it is released in October to see if the pattern of stable or growing post-graduation commitments over the past few years persists. 

The NSF SED also breaks down its data by the survey participants' demographics, including whether they are international students holding temporary visas or United States Citizens or permanent residents (PR).

While historically temporary visa holders have had lower post-graduation commitments than US Citizens or permanent residents (PR), recently, the two groups show similar percentages. The SED data from 2018, 2019, and 2020 showed virtually identical percentages across the two groups with temporary visa holders actually having higher percentages of post-graduation commitments in 2020 (70.1% to 69.8%).  In 2021, temporary visa holders showed a modest drop in percentage of post-graduation commitments to 69.4% vs US Citizens and permanent residents at 70.3%.

What can we take from these data?
​The "gap" in post-graduation commitments between temporary visa holders and US Citizens or permanent residents has narrowed over the past few years. It is important to mention here that the question about post-graduation commitments focuses on commitment within the US. So, it is possible that the closing of a gap between temporary visa holders and US Citizens and permanent residents is due to more temporary visa holders choosing not to remain in the US for employment or postdoctoral training after they complete their Ph.D.

The SED data does not fully support this hypothesis, though, as the percentage of temporary visa holders who reported an intention to stay in the US after their doctorate was 71.3% in 2021, 73% in 2020, 71.2% in 2019, and 72% in 2018. Looking at the two largest groups of international students pursuing their doctorate in the US, those from India have percentage rates intending to stay in the US ranging from 87.1% in 2018 to 86.1% in 2021 with a four year average rate from 2018 to 2021 of 86.8%. Doctoral students from China have seen a decrease in intent to stay from 2020 (80.1%) to 2021 (74.4%) specifically, declining by 7.1% year-over-year. The 2021 rate for Chinese students intending to stay in the US is also below the average of the precious 6 years of SED data (2015 to 2020) of 80.7% while the rate for Indian students has remained relatively stable (average of 86.9% from 2015 to 2020 vs 86.1% in 2021). Geopolitical tensions with China may explain these differences and it will be interesting to see how the data evolves in the years to come. 

Across the US Citizens and permanent residents in the SED data, we can examine trends in post-graduation commitments by race and ethnicity. 

Looking at the 25 year SED data trend by the race or ethnicity of the US Citizens and permanent residents, we observe white (non-Hispanic) doctorate recipients historically have higher levels of post-graduation commitments and that Hispanic, Asian, and Black doctorate recipients showed a steeper decrease in commitments from 2005 to 2015. The dip in all groups from 2005 to approximately 2015 probably reflects the impact of 2008's global financial crisis that affected employment prospects and business investment. 

Zooming in on the past five years of SED data, we can see steady increases in post-grad commitments with relatively sharp rises in those identifying as Black (8.9% increase from 2017 to 2021), Asian (8.2% increase over same period), and Hispanic or Latino (5.9% increase from 2019 to 2021). These rates compare to 4.9% increases in post-grad commitments from 2017 to 2021 and 1.9% from 2019 to 2021 across all US Citizen and permanent residents. These data seem to suggest post-graduation prospects are improving across groups and that the gap between groups has narrowed over the past five years of SED data. 

As the data shared above reports post-graduation commitments plus postdocs, SED also looks at the data by doctorate recipients pursuing postdoctoral positions specifically.

The first insight from the percentage of doctorate recipients pursuing a postdoc is that the postdoc path is much more common in certain fields. Across all fields, the percentage of doctorate recipients pursuing a postdoc in 2021 was 41.3%. In the life sciences, the percent of Ph.D. recipients pursuing postdocs has hovered around 60% to 70% over the past 25 years. Pursuing a postdoc is also quite a common post-Ph.D. path for the physical and earth sciences (~60% historically). In contrast, the percentage of engineering doctorates pursuing a postdoc was 38.5% in 2021 vs 57.9% in the life sciences and 62.2% in the physical and earth sciences. ​

The drop in postdoc commitments in the life sciences could be pandemic related as demand for those with biological/life science expertise may have risen in the for-profit sector. Indeed, the proportion of recent life science Ph.D. recipients employed in the for-profit sector (ie, industry) continues to grow and has overtaken academia as the largest sector of employment (since 2019). The divergence in employment sectors from 2019 to 2021 is particularly striking as growth in employment of recent life science Ph.D.s in industry grew by 15.3% over the three year time period while it declined by 15.3% in the academic sector. The fact that the changes across this time horizon (and visible in the graph below) are near mirror images of one another (increasing and declining at equivalent rates) suggests the possibility that industry is replacing academia as a destination for employment of newly-minted life science Ph.D.s in recent years. 

Across all recent Ph.D. recipients, industry (for-profit companies) is the largest sector of employment of those with definite post-graduation commitments and dominates employment for those in engineering, math & computer sciences, and the physical & earth sciences. Academia is still the largest employment sector for recent Ph.D.s in the psychology & social sciences, education, and humanities & arts. Furthermore, non-profit sector work is more common in the humanities & arts, psychology & social sciences, and life sciences while government employment is more common for those with Ph.D.s in psychology & social sciences, life sciences, and the physical & earth sciences than those with Ph.D.s in other fields.   

We can also observe some interesting historical trends in the employment fields of doctorate recipients over the past 5, 10, and 25 years. From 2017 to 2021, across all fields, the percentage of doctorate recipients with commitments for employment in academia decreased by 22.6%. This trend was -28.9% from 2012 to 2021 and -21.6% from 1997 to 2021. Employment in government over the same time period ranged from 5.5% to 6.9% growth. Growth in for-profit (industry) sector employment of recent doctorate recipients grew by 24.5% from 2017 to 2021, 48.5% from 2012 to 2021, and 61.8% from 1997 to 2021 across all fields and was even higher for those from the life sciences (116.4% growth from 1997 to 2021). Clearly, academia as a destination for recent doctorates is declining with industry as an increasing sector of newly-awarded Ph.D. employment. 

​The data on doctorate recipients pursuing postdocs by citizenship status clearly indicates this path is more commonly pursued by temporary visa holders, undoubtedly due to the fact that working at a nonprofit, academic institution provides a variety of visa pathways available versus the for-profit sector (from those pursuing OPT on their student F1 visas to J1 scholar visa options and H-1B visas that are "uncapped" vs those available in the for-profit sector).

The sharp increase in postdoc pursuit in both US Citizens/PRs and temporary visa holders after 2008 suggests a pivot during and after the great financial crisis of that year which slowed the economy and limited career opportunities in the for-profit and government sectors. Postdoctoral positions were potentially "safe places" to ride out the rough economy. And while the percentage pursuing postdocs dropped relatively steeply for temporary visa holders after 2010, the rates remained elevated for US Citizens and permanent residents from 2011 to 2021 (37.5% pursuing postdocs) and rates during this eleven-year time span were 30% higher than that seen from 1997 to 2007 (28.8% pursuing postdocs).

We also see a bit of sign of the COVID-19 pandemic's impact in the data from 2020 to 2021 where the percentage of US Citizens or permanent residents pursuing postdocs increased by 6.25% year-over-year while the increase was 9.9% for temporary visa holders. It will be interesting to see if the 2022 SED data shows that COVID's impact on this metric subsided or persisted.

There are vast differences in the percentage of US Citizens and permanent resident doctorate recipients pursuing a postdoc by their race/ethnicity. Rates have historically been highest in those identifying as Asian and the rates have climbed steadily for White, Non-Hispanic individuals and those identifying as Hispanic. For Black survey respondents, the percentage of doctorate recipients pursuing postdocs in 2021 stood at 25.4%. This compared to a rate of 39.9% in White, Non-Hispanic; 41.5% in Asian; and 41.4% in Hispanic respondents. 

I will turn to 2021 Survey of Doctorate Recipients (SDR) data to further explore postdoctoral demographics as well as compare the demographics of recent Ph.D. recipients (data from the SED) to those in postdoctoral positions (data from the SDR). 

In raw numbers, nearly 5,000 of the 27,150 postdocs surveyed across all fields in the 2021 SDR were in their postdoc more than 5 years after receiving their doctorate degree. It is notable that nearly a quarter of those postdocs with doctorates in the life sciences were in postdocs 6 or more years from receiving their degree, a rate (24.5%) nearly twice that seen in the physical sciences (12.6%) and engineering (12.7%). 

Across all individuals 5 or fewer years from their Ph.D., 15.7% (22,200 of 141,750) were employed as postdocs and this percentage rose to 28.5% for the biological, agricultural, and environmental life sciences and 22% for the physical sciences. For those who earned an engineering doctorate within the last 5 years, only 10.5% were employed as postdocs. Across all science doctorates surveyed in the 2021 SDR, 19.7% of postdocs were 5+ years from their Ph.D. and this percentage rose to 24.1% in the biological, agricultural, and environmental life sciences. 

Across all those reporting they were in postdoctoral positions in the 2021 SDR survey (n=27,150), 53.2% were US Citizens while 46.8% were non-Citizens. Of engineering doctorate holders in postdocs surveyed, 70.9% were non-US Citizens. Mathematics and statistics (64.7%) and physical sciences (54.1%) postdocs were also majority comprised of non-US Citizens. In the biological, agricultural, and environmental life sciences 60.8% of postdocs surveyed were US Citizens. The percentage of postdocs who were US Citizens was also high in the social sciences (66.7%), computer and information sciences (66.7%), and psychology (82.4%).  

Across all fields, postdocs are 58.6% male. In engineering, nearly 3/4 of postdocs are male (74.7%) while the ratio is 2/3 for the physical sciences (66.7% male). Over 3/4 of mathematics and statistics doctorates in postdoctoral positions are male (76.5%). Those with doctorates in the biological, agricultural, and environmental life sciences working in postdocs are 53.9% male. ​

Ethnicity of US Postdocs vs Doctorate Recipients
The SED reports on the race and ethnicity of those earning doctorates in the US each year. Looking at the SED from 2001 and 2021, we observe growth in the share of Ph.D.s awarded to those identifying as Asian, Black, and Hispanic or Latino with doubling of Ph.D.s awarded in the later group from 2001 to 2021.

In the SDR data from 2021, 6.3% of those in US postdocs identified as Hispanic/Latino, 3.1% as Black, 41.3% as Asian, and 47.2% as White. ​

If we compare 2021 SED to SDR data we see that while 9% of doctorate recipients were Hispanic/Latino, 6.3% of postdocs identified as such, resulting in a ratio of postdoc/PhD recipients identifying as this ethnic group of 0.7 (the postdoc composition of this group is 30% less than its composition in the PhD recipient group). Calculating a similar metric for other races/ethnicities, we get ratios ranging from 0.4 for Black to 4.3 for Asian (and 0.7 for White). Given the SDR data on postdocs does not breakdown race/ethnicity by US Citizenship status, we can't perfectly map it to the SED data. 

Looking at the SED data more closely, it reports Ph.D. recipient data by race/ethnicity and US citizenship status, showing that in 2021 of those identifying as Asian, 20.7% were also US Citizens or permanent residents and in total 27.9% of all Ph.D. recipients from US universities identified as Asian in 2021. If we use the 27.9% of all doctorate recipients in our ratio of postdoc/PhD recipients for Asians, we get a ratio of 1.5 or nearly double that of While recipients.    ​

What is also obvious in this rather crude analysis of postdoc/PhD recipient population proportion is that Black doctorate recipients are not in postdoctoral appointments at the same rates as White, Hispanic/Latino, or Asian individuals and that Asians appear over-represented in postdoctoral positions relative to other ethnic groups.  ​

The 2021 SED data reports median salaries for doctorate recipients (ie, newly-awarded Ph.D.s) by employment sector and field of degree. Collapsed across all fields, the median salary for a doctorate recipient in 2021 was $90,000 and ranged from $68,000 in academia to $115,000 for industry careers. There was also large divergence by Ph.D. field with computer and information sciences doctorates earning a median of $145,000 across all employment sectors in 2021 vs $55,000 in the humanities. 

Postdoc salary has become a hot topic in recent months and the 2021 SED data also reports median postdoc salaries by Ph.D. field. 

The median salary of a recent computer and information sciences doctorate working not as a postdoc is 123% more than the median postdoc salary for someone from this field. The gap is narrower in other fields but across all fields a position outside a postdoc has a median salary 68% higher than a postdoc median salary.   

The SDR data from 2021 allows us to get a better glimpse at median annual salaries across a range of fields and by seniority of respondents (years since doctorate). 

Across all fields, you can see a clear upward trend in the median annual salaries of doctorate recipients as they become more senior (are further out from receiving their degree). Those with engineering doctorates consistently out-earn most of the other sciences while the computer and information science doctorates (dashed gray line, above), show more volatility in the upward trend of earnings as they move further from receiving their degree. Math and statistics also shows a small dip in earnings trajectory for the 16-20 years from degree group. Given these data are from the 2021 SDR, the time period in which that group earned their degrees was most likely 2001-2005 and could reflect the remnants of the "dot-com bust" of the early 2000s where the NASDAQ-100 (an index of mostly US technology stocks) bottomed in October 2002.

The 2021 SDR also reports median salaries for faculty positions of respondents by field of doctorate and faculty rank (assistant, associate, or full professor).

The SDR data asks respondents to report on their primary work activity across several categories including research & development (R&D); teaching; professional services; & management, sales, or administration. Many recent Ph.D. recipients think that the primary activity they will perform is R&D or teaching but the SDR data show that the percentage of individuals reporting those two activities as their primary work activity has remained flat or declined over the past few years. 

The dotted lines in the graph above reflect the percentage of SDR respondents in 2017, 2019, and 2021 (three most recent surveys as the SDR is collected every two years) who indicated a role other than R&D and teaching as their primary work activity. You can see across three broad Ph.D. fields (life sciences, physical/earth sciences, and engineering) the percentage reporting "other" work as their primary activity has increased. In fact, this percentage of those reporting "other work" is equivalent to those reporting R&D as their primary work activity in engineering and physical/earth sciences and approaching equivalency in the life sciences. In other words, more Ph.D.s are working in roles where their primary activity is something other than research/development and/or teaching. 

What are some of these other primary work activities? 
The 2021 SDR data found 21.3% of life science Ph.D.s's primary work activity is in management, sales, or administration with another 11.2% reporting professional services. Physical/earth sciences Ph.D.s reported a similar level of primary work in management, sales, or administration (21.2%). This percentage was 20.3% for those with engineering Ph.D.s. So, roughly 1 in 5 Ph.D.s in science and engineering work primarily in management, sales, or administration. This finding suggests the importance of Ph.D.s thinking about how they can build transferrable skills like communication, leadership, and project management to help set themselves up for success in these areas. 

While a lot of data were shared in this piece, I have only scratched the surface on the wealth of information available through NSF. You can explore some of their reports on the 2021 SED as well as COVID impacts when comparing 2019 to 2021 SDR data to learn more about trends in the Ph.D. workforce. 

Some key insights (and my thoughts/comments) from the data in this piece include:

• ​Little apparent effect of the COVID-19 pandemic on Ph.D. "post-graduation" commitments suggesting Ph.D. talent is often in demand (though postdoc pursuit may have spiked a bit in some fields as a result of the pandemic). 
• Relative growth in the percentage of recent Ph.D.s with definite post-graduation or postdoc commitments over the last few years (2017 - 2021) - Perhaps institutions are doing a better job connecting grad students with resources and the knowledge to navigate the job market proactively?
• The gap between temporary visa holders and US Citizens and permanent residents with definite post-graduation commitments has narrowed over the past few years (since 2018), this could be the result of more openness from employers to sponsor work visas or more international students not wanting to stay in the US for employment (w/ some early signs of this from Chinese graduate students).
• Gaps in US Citizens or permanent residents with post-graduation commitments from different ethnic and racial groups narrowing over the past few years, which may suggest better access and dissemination of information on the job search process that might have been more implicit in the past (ie, uncovering the hidden curriculum). 
• A decline in the number of individuals pursuing postdoctoral positions in the life sciences and physical & earth sciences over the years but an increase in the percentages of engineering, psychology & social sciences, and education doctorates pursuing postdocs.
  • "Peak postdoc" may have been reached in the life sciences and physical & earth sciences around 2010.
  • Potentially, higher scholarly productivity expectations has resulted in a postdoctoral position becoming more common in other academic fields. 
• Relatively low levels of Black Ph.D. recipients pursuing postdoctoral training.
  • Is the way we hire postdocs (mostly via networking) hurting certain under-represented groups and/or is the academic career path of less interest to these individuals? 
• A sizeable number of individuals are in postdoctoral positions 6+ years after receiving their Ph.D., especially in the life sciences. 
  • While a postdoc is supposed to be a relatively short-term, temporary training position, the data suggest some individuals can be in them many years after their Ph.D. was awarded.  
• The for-profit sector (industry) as the main employment sector of most recent Ph.D.s.
  • Better pay and less perceived job stress may be pushing Ph.D.s to pursue careers outside higher education/academia. 
• Differences in median salaries for Ph.D. recipients working in different sectors of employment. 
  • Data on median salaries across employment sectors as well as for postdoctoral and faculty positions by field of doctorate can be instructive as individuals make decisions on what fields to pursue in graduate school and/or which career path(s) to pursue, post-Ph.D..
• The rise of primary work activities beyond teaching and research & development since 2019, signaling a need for Ph.D.s to develop transferable skills like leadership, project management, & communication.

I thank the NSF for collecting and sharing these data. Leveraging this information and examining longitudinal trends helps empower both prospective and current graduate students, postdoctoral scholars, faculty, and administrators with knowledge of the state of the Ph.D. labor market and evolving scientific workforce. Only through knowing where we are currently at in terms of the demographics of the scientific workforce and the possibilities of what is out there for areas of Ph.D. employment can we chart a path to where we want to go both individually and as a society. 

Future of Work, Opinion

Resistance is futile. The artificial intelligence revolution is underway. All hail our robot overlords.

Too much to start off a piece on the future of work? Perhaps, but many people have been feeling this way over the last few months. 

Late Fall 2022 was rocked by the public release of ChatGPT, an online chat bot from the company OpenAI that leverages large language models to generate predictive text "responses" to user-entered prompts. The technology has captured the public's attention with over 100 million users of the product within 2 months of launch, the fastest user uptake of an internet-based application/product in history.  ​

And on March 14, 2023, OpenAI announced the launch of the even more powerful GPT-4, which they claim can score in the 85th or higher percentile on the LSAT, SAT, and AP Biology exam. During a livestream demo of the platform (which garnered over 1.4 million views in less than 18 hours), the company showed the power of this next version of their technology, which can perform a range of functions from assisting with writing and troubleshooting computer code to analyzing an image. The demo also highlighted how GPT-4 can take a human-sketched and written design and create website html code or advise on one's taxes (by understanding and acting on the thousand-page US tax code). The range of capabilities and versatility of this model's output is quite astounding! 

Understandably, the release and promotion of ChatGPT, GPT-4, and other "generative artificial intelligence (AI)" products (Meta launched LLaMA in late February 2023 and Google's Bard and Anthropic's Claude both launched in March 2023) is being met with both awe and fear. There is a sense that the current "AI arms race" between companies and governments could lead to the technology outrunning needed safeguards and ethnical discussions around its use. The rapid pace of advancement of this technology has left many to make the case we should slow down on accelerating its deployment, including a statement signed by over 1,000 technology and business leaders urging caution in growing the size of large language models until they are better understood and more regulatory and security guardrails are put in place. 

Even the founder and CEO of OpenAI, Sam Altman, is unsure where this new technology will lead. Though he acknowledges generative AI will displace some human work in the near future, he is hopeful that it will ultimately create better jobs and more fulfillment for humanity. His recent interview with ABC News is shared below and you can watch a longer interview with him and Open AI's Chief Technology Officer here. ​

Versatile AI in a "Black Box"

The consulting firm Gartner has published a report on use cases for generative AI in a variety of industries and sectors. In their report, they highlight how AI could be used to assist in drug design and materials science research, including optimizing the design of various industrial components or semiconductors to maximize a particular use case or efficiency target. In addition, the investment firm ARK's 2023 "Big Ideas" report has made the case that advances in AI are the key catalysts to advancing the development of a variety of innovations from precision therapeutics to robotics and autonomous transportation. 

And if this output becomes increasingly relied on to aid in consequential decisions (think AI-assisted mortgage determinations), the inability to understand the basis from which the model generates output is problematic. It brings up the question of whether all output, products, or decisions that affect society should be rendered by a model that weights various pieces of input through an incredibly large neural network with hundreds of billions of parameters.

​Can all our problems be solved with more data and more computing power? 
Spoiler alert: No.​​

"Everyone will have a their own white collar personal assistant."

Microsoft founder Bill Gates said as much in a recent blog post about the power and potential of AI. It is not difficult to see how generative AI could be very helpful as an assistant to humans, helping them be more creative and productive.

Thanks to backing of OpenAI by Microsoft, ChatGPT-like technology is being integrated into the Microsoft 365 Suite of business software (Word, Excel, Powerpoint; which they have dubbed "Copilot") and their Bing search product. And recently Zoom announced an AI integration in their video meeting platform. AI as a productivity assistant is upon us. 

And who wouldn't be excited for the day when Outlook or Gmail offers to author responses to your 50+ un-replied-to work emails in a matter of minutes? Let AI handle the boring, administrative things while you focus on other more pressing matters. Though, this does not speak to the complexities around how the human reading your message on the other end feels about it, especially if they know it was written by AI. One could quickly see that this results in some weird future where human beings are not "in the loop" of these digital communications at all. AI written content being "read" by AI models to be responded to with AI and on and on it goes....In this infinite communication loop, what is the point of having a human involved at all? Does someone need to interpret the exchange and act? Could that one day be an AI decision maker (or human decision maker "assisted" by AI)?

​This quick little thought experience brings up the philosophical point around what are human beings for in a knowledge economy that my one day be driven predominantly by AI that is more efficient and effective at a range of data-based tasks? 

Productivity & Progress

Our modern, 21st-Century American economy is quite fixated on productivity. In fact, many news outlets lament a recent drop in worker productivity, defined by the Bureau of Labor and Statistics as how much total economywide income is generated (i.e., for workers, business owners, landlords, and everybody else together) in an average hour of work. Despite the recent decline in this metric in the past few years, it is inarguable that at a global scale, worker productivity has increased greatly over the past 50 years along with our technological progress.  ​

In theory, increased productivity should lead to increased prosperity, right? This is only true if productivity gains are shared across a society. However, data show that the gap between the average workers' pay and overall productivity in the United States has grown dramatically since the 1980s. While productivity from 1979 until 2021 grew by 64%+, average compensation grew at only a 17% pace. In short, the "returns" generated from increased productivity have not been shared with the average worker in America. This fact shocks no one and reinforces the argument that inequality (in the US and beyond) has accelerated since the early 1980s. 

One open question from these data, then, is whether the gains in productivity and efficiency to come from generative AI will be shared across society or concentrated in the hands of a few? The fact that OpenAI has "open" in its name and has, at least for now, made its ChatGPT technology available to anyone perhaps signals a more egalitarian approach to sharing this technology more equally than many that came before it. It is important to note, though, that while the interface is "open" the source code and details behind the data used to train the model ​are kept carefully under wraps. 

Companies like OpenAI suggest that these GPT technologies will make many workers more productive and efficient. The fact that anyone can access and use ChatGPT would suggest that anyone and everyone can become more productive by using it. This sounds like a great thing but how much can human performance be optimized? If we are talking about optimization, is that something better left to the machines and algorithms anyway?  ​

​Job Automation 

Studies investigating the effects of robotic automation on industrial and manufacturing jobs found evidence that the deployment of industrial robots reduced both the number of human workers and their wages in these industries. Then came the dawn of generative AI that demonstrated automation of creative and knowledge work, generating stunning visual images and often clever and compelling written words in a matter of a few seconds. This advancement is so new we cannot yet measure its effects but one can easily see that "automation" can replace more than routine, manual manufacturing work.

Just this month, OpenAI and researchers at the University of Pennsylvania released a pre-print (not peer-reviewed) publication titled "GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models". In this study, they assessed occupations based on their correspondence with the current capabilities of the Generative Pre-trained Transformer (GPT) models behind technology like ChatGPT and GPT-4. They found that approximately 80% of the U.S. workforce could have at least 10% of their work tasks affected by the introduction of GPTs, while around 19% of workers may see at least 50% of their tasks impacted. They go on to state: "The influence spans all wage levels, with higher-income jobs potentially facing greater exposure." 

And just this week (March 26, 2023), Goldman Sachs's Economics Research released a report predicting that two-thirds of US jobs are exposed to automation by AI and going on to state that it believes ~7% of current US jobs could be replaced by AI (which, based on a current US labor force size of 166 million, equates to 11.5+ million people - more than the population of the state of Georgia). The positions at greatest risk according to their report: administrative support, legal positions, and architecture and engineering jobs. Meanwhile, they found the jobs with the lowest exposure to AI automation included those in cleaning and maintenance, installation and repair, and construction. On a more positive note, the Goldman Sachs report believes AI could increase the total value of goods and services created worldwide by 7%. So, while some humans may be rendered redundant by AI, overall value in the economy could be increased, raising the question we posed earlier: who will see the economic benefits of AI and who will bear the costs?

The findings of these studies are perhaps not all that surprising as the world gets a better sense of what GPTs can accomplish. In some ways, administrative and knowledge work is the most automatable, even if there needs to be large advances in current technology to get to a (dystopian?) future where AI has replaced all ​human knowledge work.

The Future of Work is More Human

As AI becomes increasingly better at producing digital output, including images generated from programs like DALL-E or DreamStudio or computer code from Copilot, it is important to remember that there is still a physical world with many needs and problems that AI cannot yet act on effectively. Some jobs and tasks currently performed by humans will be very difficult if not impossible to automate away. Human skills and professions that emphasize physical interaction and engagement with objects in the world will remain essential as long as we live in a physical world with others (but the creation of a functional metaverse could change that). One could imagine a not-too-distant future where the skilled trades (which are already seeing a renewed interest and level of appreciation in younger generations) gain even more respect from society. A robot is not going to fix your plumbing or electrical issue any time soon. Construction work is another example of work that seem un-automatable.​

Ironically, tasks performed by the "trade professions" that many may view as "routine" but require presence in and manipulation of the physical world are much harder to automate than many futurists would have predicted a few decades ago. And perfecting the autonomous car has been exceedingly difficult even with vast amounts of resources devoted to the effort. Maybe those truck driver jobs are more safe than initially thought? Bottom line: acting on and operating in the physical world is really hard for current AI. ​

Another large category of work that I think will be very difficult for AI to replace is in the caring fields - think healthcare, childcare, counseling, and even teaching (especially young children). These caring professions involve interacting with human beings and even if one theoretically could automate this type of work, I do not think humanity would be very keen on entrusting the care of its children, elderly, and sick to robots and automated systems anytime soon. Knowing that another human being cares about you and your loved one's well-being is critically important and while generative AI can seem human and caring, it is important to remember that this technology does not have intentions or motives. Current AI literally does not "care" about anything. 

So, while the late 20th Century economy valued data science and computer skills, the future of work will reward those that are handy and humane. Both technical skills that center around operating in the physical world and interpersonal skills that help one work with, understand, and assist other human beings will become increasingly important to thrive in the future. This shift in what types of work is valued could have massive societal implications. 

Richard Reeves from the Brookings Institute has made a case for the growth of HEAL jobs: health, education, administration, and literacy and the fact that many of these professions are only ~25% occupied by men. He speculates that many men have shunned occupations like teaching and social work due to low pay but as labor shortages in these "hands-on" fields continue, demand may push up compensation. This may be even more true as AI replaces careers in software, computer science (some startup companies have already indicated they are using GPT-4 technology to reduce the need to pay human coders for services), finance (a recent pre-print suggests ChatGPT can help you pick a diversified investment portfolio), and others which have been overwhelming held by well compensated men. It is possible that the rise of AI will signal an increased societal importance placed on the HEAL fields. These professions and those of the skilled trades have always been critical to a functional society and it may take the rise of AI for more people to appreciate that point. I think, in the end, that will be a good thing. 

A Post-Work World?

​Even if the demand for HEAL professions and skilled trades rises in the years to come, the labor force will be forever changed as a result of generative AI technology and sooner than many may think. An interesting wrinkle in all of this is that if it is the knowledge workers whose occupations disappear will there be a larger push by the educated "elite" to support the unemployed and perhaps push for a universal basic income? Sadly, when blue collar workers in the US lost their jobs as a result of deindustrialization and globalization in the 1980s and 1990s many seemed unconcerned. When disruptive AI comes for the careers of journalists, computer programmers, and marketers, those influential individuals will definitely make some noise. Maybe they will be loud enough to help reshape our society to be less focused on work and wages than we have come to understand them? 

While a world without "work" seems almost unimaginable, it is important to point out that this mostly implies a world without humans performing some work. There may come a time soon when work that is tedious, laborious, and often undesirable by people will be replaced by automation, AI, and machines. This would, in effect, free people from performing these tasks. Instead, they may be able to focus instead on activities they enjoy (hobbies or creative pursuits) and that, at least in theory, can be good for society writ large - volunteering, community engagement, and care-giving, among others. 

​Image generation programs like DALL-E (from OpenAI) and DreamStudio (from Stability AI) and the advancement of AI video creation tools would suggest that creative work will also be vulnerable to automation. Alternatively, some have argued these technologies will make humans more creative. Though, we may need less creative types who are paid for their services if AI is doing most of the heavy lifting. Imagine a future where AI can create a unique, customized movie generated to your exact tastes. Would that lead to us amusing ourselves to death or being more glued to our screens?

​In a future of endless content and diversion, will we still seek to make an impact on the world?

Work Worth Doing

Far and away the best prize that life has to offer is the chance to work hard at work worth doing. - Theodore Roosevelt

Teddy Roosevelt's quote highlights a big existential question we face as AI is increasingly able to do more of our work: What is work for?

It could be argued that many human beings engage in "work" for meaning. They want to justify to themselves that their life has purpose and impact and this is often reflected in the work they do. The definition of "work" in the future may change, though. While today we think of work as an occupation one performs in exchange for wages to subsist on, perhaps the future of work is work that is more focused on contribution to the betterment of others that is decoupled from any monetary compensation? This idea seems very foreign to many but who says human work has to be about delivering measurable economic value? 

The increasing efficiency and productivity of AI suggests we shouldn't try to compete there. Let AI do what it is good at: optimizing parameters, testing models, and generating creative content. Freed from the need to "produce," humans may be able to think more about what they really care about and how they want to live their lives. Automation and the end of work as we know it may free us from a hyper-capitalist society where all too often our value is measured by what we produce. Instead, a future where AI worries about industrial and knowledge production at scale could free people from thinking of themselves as economic assets or liabilities on society. Rather, we could focus more on what we love to do rather than what we have to do.

This could lead to a place where everyone pursues their passions. We might also choose to focus on tasks and "work" that we know AI can "do better" but that we find fulfillment in doing ourselves. Steven Hales touches on this idea nicely in a recent piece entitled "AI and the Transformation of the Human Spirit" where he makes the point that successful authors still write despite their financial position and technology has made it such that most people don't need to bike 5 miles along an open road on the weekend (a Peloton bike is so much more efficient) or mountain climb but they do it anyway. I can't say it better than he does in the quote below:

In addition, free from the need to produce we might be able to re-engage with our fellow humans and be able to have deep and meaningful conversations with others to find common ground and aspirations for our society. To realize that we are all human and deserve basic respect, dignity, and support. We could work to repair our societal and community institutions like schools, civic groups, government agencies, legislative bodies, and so much more with all this new-found time. ​

In an ironic way, the rise of AI could bring us closer together as a species by better understanding what it means to be human. And while in the interim generative AI has the potential to produce more misinformation and destructive content, we are increasingly realizing that a negative digital world is not what we want. I believe much online negativity and tribalism has been fueled by fear of the world's resources and opportunities being zero-sum...that there is not enough success or money or power to go around. In a future where AI has freed us of the need to "produce to survive" we may be able to evolve past the scarcity mindset that has been a reality for our species from the beginning. It will be a paradigm shift and certainly take time but I believe in the end this technology will produce more abundance for the human race. We will still need to do the human work of engaging with and supporting our fellow man and employing the ethical use of AI in our society to realize the benefits of this optimistic future, together.  

Steven Hales concludes "AI and the Transformation of the Human Spirit" with something we all should think more about in this brave new world we are entering.

The Future is What We Make It

One fact that I think gets lost in the wonder that is generative AI is that is a product of virtually all of us. Yes, programmers and computer scientists created the neural networks and reinforcement learning models that lead to the ability for the AI to generate output. But it was our collective knowledge contribution via the internet that fed these models with vast amounts of data generated by billions of humans over thousands of years sharing their art, ideas, knowledge, worries, fantasies, hopes, and dreams with the world. Out of these models has come something "human-like" but not necessarily human. We must remember the difference. While generative AI can produce wonders and probably will lead to more productive generation of media to entertain us and knowledge to empower us, it can also be leveraged by bad actors to turbocharge our fears and anxieties. 

This technology is, in a way, a fun-house mirror for our humanity. It reflects back at us surprising, scary, and wonderous things. It could enslave us in a future where we are subjects of the black-box algorithm that strives for efficiency and productivity whatever the costs. Or, it could make us more human and free us from the drudgery of many tasks, leaving us more time to focus on helping and caring for others and being in community with our fellow man.

What will we do with the time AI may give back to us?
​How will we be responsible stewards of a technology capable of immense constructive and destructive impact as it continually improves over the coming months and years?  ​

In the end, we will get out of this technology whatever we collectively feel is most valued and important to us. I hope we choose humanity over optimization and oppression.
​Our future depends on it.

More from the Blog:

• To Be Rather Than To Seem
• The End of Work as We Know It: How an increasingly automated world will change everything (from December 2019)
• Precarity, Competition, and Innovation: How economic systems and societal structures share our future

For Further Reading

• AI Is Like … Nuclear Weapons? The new technology is beyond comparison.
• Big Ideas 2023 from ARK Invest
• What Have Humans Just Unleashed?
• Welcome to the Big Blur: Thanks to AI, every written word now comes with a question.
• Why All the ChatGPT Predictions Are Bogus
• The Economics of AI
• The case for slowing down AI
• Preparing for the (Non-Existent?) Future of Work (Brookings Institute Report)
• Robots and Jobs: Evidence from US Labor Markets (NBER paper from 2017)
• Post-work: The radical idea of a world without jobs
• The Crisis of Social Reproduction and The End of Work
• ​Redistributive Solidarity? Exploring the Utopian Potential of Unconditional Basic Income
• Enjoy the Singularity: How to Be Optimistic About the Future
• How to be a leader in an AI-powered world

Recent Pre-Print and Other Publications on GPTs

• Predictability and Surprise in Large Generative Models
• GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models
• Sparks of Artificial General Intelligence: Early experiments with GPT-4
• Theory of Mind May Have Spontaneously Emerged in Large Language Models
• GPT-4 System Card

Book Recommendations

• Broken: How our social systems are failing us and how we can fix them​​
• ​Futureproof: 9 Rules for Humans in the Age of Automation

Listen to:

• Andrew Yang's Forward Podcast interview with Kevin Roose on "Futureproofing Your Career in the Age of ChatGPT"

In last month's blog post I discussed how our perspective matters in how we interact with and see the world. As I was exploring research to cite in that piece I came across some very interesting work related to how how a person's mindset can affect them, physically. 

Much of this work comes from Alia Crum, an Associate Professor of Psychology at Stanford University. The Stanford Mind & Body Lab she directs studies how subjective mindsets (e.g., thoughts, beliefs, and expectations) can alter objective reality through behavioral, psychological, and physiological mechanisms. Her first publication, Mind-set Matters: Exercise and the Placebo Effect, found that informing female hotel room attendants that their work cleaning rooms was good exercise that satisfied the Center for Disease Control and Prevention's recommendations for an active lifestyle perceived themselves getting significantly more exercise 4 weeks later than a control group despite no overt change in their actual physical activity. Informing the attendants that their work was good exercise also affected their physiology measured at the 4-week time point. In fact, the subjects in the informed group lost an average of 2 pounds, lowered their systolic blood pressure by 10 points, and were significantly healthier as measured by body-fat percentage and body mass index.

​This study is a remarkable demonstration of how perception and belief an affect not only how one perceives their actions but also how this impacts their bodies and health. Crum has gone on to examine other interesting effects of mindset and beliefs on human physiology including how a milkshake perceived as more caloric and decadent increased participants' feeling of satiety ("fullness") and reduced ghrelin levels (a physiological signal for satiety) more than a milkshake labeled as healthy/diet despite the fact the milkshakes were identical in their make-up. The simple belief that one shake was more decadent and rich (despite it not actually being so) led to a physiological signal of more "satisfaction". Beliefs are powerful things.

And while certainly these findings are interesting and potentially impactful in how we think about food and exercise, Crum and others have also demonstrated the power of mindset on our mental state and ability to function productively in the world.

​For example, stress can both enhance and hinder human performance and work by Crum and colleagues show that one's stress mindset can impact both physiology and behavior. Based on responses to a scale developed by these researchers (Stress Mindset Measure), individuals fall into either a “stress-is-enhancing” or “stress-is-debilitating” mindset by default. Importantly, though, information presented to individuals that emphasize the enhancing nature of stress show improvements in self-reported health and work performance. Additionally, the authors found that individuals with a stress-is-enhancing mindset have a stronger desire to receive feedback on their performance and show more adaptive cortisol (stress hormone) profiles under acute stress.

Crum's stress work indicates the importance of mindset on how we respond to challenges in the world. One of her most recent publications, though, takes her lab work out into the real world. Specifically, they investigated differences in how individuals viewed the COVID-19 pandemic at its outset in Spring 2020 and the impact these varied viewpoints had on a variety of measures collected from them 6 weeks and 6 months later. Over 20,000 American adults participated in this study at intake (which took place on the very day the World Health Organization officially declared COVID-19 a global pandemic: March 11, 2020) with analyses investigating subgroups that completed the follow-up assessments at 6 weeks (May 2020; n=9,643) and 6 months (October 2020; n=7,287) post initial assessment. A total of 5,365 COVID-negative participants completed all three surveys and were included in the subsequent longitudinal analyses by the team.

Study participants' mindsets (using a modified version of the Illness Mindset Inventory, for more see) about the pandemic were categorized along three dimensions:

• Catastrophe Mindset: The COVID-19 pandemic is a global catastrophe that is wreaking havoc on our society.
• Manageable Mindset: The COVID-19 pandemic can be managed so that people in our society can live life as normal. 
• Opportunity Mindset: The COVID-19 pandemic can be an opportunity for our society to make positive changes.  

​Importantly, mindsets differed between individuals and within individuals over time (some individual's mindsets shifted across the timepoints assessed).

Here is an excerpt from the discussion section of their paper explaining their findings:
"Those who endorsed the catastrophe mindset more than others took the situation more seriously; they stayed home, washed their hands, and (when it was recommended) started wearing a mask. Interestingly, this appeared to be at the expense of other aspects of their wellbeing.

This contrasts with the effects of the manageable mindset. Despite maintaining high levels of wellbeing during the pandemic, people who adopted the manageable mindset to a greater extent than others were much less likely to prioritize these CDC recommendations. As such, endorsement of this mindset may reflect an attempt to deny the reality of the global pandemic and a refusal to engage with it in a socially responsible way. Over time, as people adjusted to the changes necessitated by the pandemic, it may have become more adaptive.
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The opportunity mindset seemed to provide the best of both worldviews; those who adopted this mindset to a greater degree compared to others staved off major declines in wellbeing without subverting the behaviors necessary to engage with the pandemic in a socially responsible way."

Indeed, framing stressful and challenging situations as an opportunity is crucial to aid us in persisting in activities despite the perceived and real barriers we face. And viewing the stress associated with life as enhancing can help us channel our stress to productive efforts.

​For many seeking to enter the world of work, the modern job search is one of those stressful experiences than can benefit from a mindset shift. 

Your mindset affects your career. 
​Data show that students with a lifelong learning mindset (ie, a growth mindset) receive higher supervisor ratings of their performance in a co-operative education program and report higher levels of job satisfaction, work engagement, and job-related self-efficacy in their careers after graduation. In addition, they receive more promotions in their careers.

​A study of Duke University MBA students mirrored these findings: those with an optimistic attitude about life (assessed at the beginning of their graduate program) received more internship offers, had better employment prospects at graduation, and were more likely to be promoted 2 years after graduation.  

Your mindset, uncertainty, and the future. 
​We must acknowledge that while optimism and a growth mindset can help you navigate the world and your career more effectively, we are living through a time of rapid technological progress and change. The rise of artificial intelligence, machine learning, large language models, and more have added increased levels of anxiety amongst knowledge workers (a topic I will discuss in March's blog post). We must remember though, that by its very nature, the future is uncertain and unpredictable. Dealing with this uncertainty and change by abandoning your agency is not a winning strategy, however. 

Regardless of what is happening in the ever-changing external world, we must believe that we have, at minimum, control over our mindset and, as a result, believe that things can get better for us despite the stress and uncertainty we face. Cultivate optimism and a growth mindset. 
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​Indeed, optimistic individuals tend to have better health prospects and live longer and cultivating a growth mindset is associated with increased subjective well-being & health and relationship & job satisfaction. ​

I spend much of my working days thinking about how to help individuals with Ph.D.s navigate their careers. It is both a reflection of human nature and a sign of the times that some of the most educated individuals in society are stressed, anxious, and pessimistic about their job prospects.

​Some of this is surely rooted in how academia has constructed graduate and postdoctoral training (ie, an apprenticeship model) as well as actual barriers to work that exist for international students and scholars needing work visas to be employed in the United States, for example. 

A great deal of job search anxiety comes from the fact that humans are often wired to focus on what they don't have versus the attributes they do possess (see last month's post and a discussion of the negativity bias). We all have valuable skills and perspectives to share but we have to believe this is the case before we can convince others of these facts.

In addition, we need to work to channel our stress and unease about a job search into productive efforts (ie, view stress as enhancing vs debilitating). Instead of allowing our feelings of inadequacy to push us toward a state of inaction or resignation remember that growth and development is part of life. Just because you aren't good at something yet doesn't mean you can't develop that skill or competency.

​Take a growth mindset to developing your growth mindset. Construct a plan to enable you to assess your skills, determine where you need to develop, and chart your future, ideally before you enter a job search.  

To return to the fundamentals of your mindset, a critical first step to making progress in your career, job search, and life is believing you have something to offer and contribute. Focusing on your strengths and unique experiences can help and as we have seen in some of the data shared in this piece, simply reframing your beliefs (in this case about your job search) in an affirming light - I have something to offer and contribute - can make all the difference in your experience and even, perhaps, your outcomes.