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Reflections Blog

Optimization, Oppression, and Optimism In The AI Age

3/30/2023

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Future of Work, Opinion
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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. 
​The ability for large language models to ingest a large amount of data and have their parameters weighted to achieve certain outputs makes them incredibly versatile and powerful. One interesting twist, however, is that even the developers of generative AI models and interfaces aren't entirely sure how they produce their output. The means by which these models produce data often involves complex neural networks and reinforcement learning approaches that result in very complex "routes" from input to output that are not initiative for a human observer to understand (though some researchers are working to make these neural networks more explainable). Ethical questions have been rightly raised regarding whether bias in these models or the data they were trained on could result in flawed output. 
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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? 
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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?  ​
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​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 seeds of societal change planted during the COVID-19 pandemic, specifically a demonstration that much knowledge work can be performed remotely, may have also accelerated the ultimate replacement of this type of work by AI. Many white-collar technology workers have resisted the return to office work over the past few years, removing themselves from physical interactions with co-workers and supervisors. In many ways your work output can be dissociated from your humanity when it is transmitted to your employer and customers via electronic means. The employer and coworkers often don't experience a remote worker as fully human but rather pixels on a Zoom screen or text messages on Slack. In a few years time, AI may be able to conjure a digital collection of pixels that mimic a "real" human over video that we won't even be able to tell the difference. For years we have been increasingly dissociating the physical world from the digital one and, thus, replacing pieces of the physical world (ie, human employees) with digital options (AI workers) seems inevitable. The bigger question is how much replacement is possible and ethical.  
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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. ​
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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. 
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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?
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Image generated via DreamStudio using prompt: "robot running past a man in a race, photo art, HQ, 4k"
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:
When AI lifts the burden of working out our own thoughts, it is then that we must decide what kinds of creatures we wish to be, and what kinds of lives of value we can fashion for ourselves. What do we want to know, to understand, to be able to accomplish with our time on Earth? That is far from the question of what we will cheat on and pretend to know to get some scrap of parchment. What achievements do we hope for? Knowledge is a kind of achievement, and the development of an ability to gain it is more than AI can provide. GPT-5 may prove to be a better writer than I am, but it cannot make me a great writer. If that is something I desire, I must figure it out for myself. - Steven Hales
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. ​
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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.
We are living in a time of change regarding the very meaning of how a human life should go. Instead of passively sleepwalking into that future, this is our chance to see that the sea, our sea, lies open again, and that we can embrace with gratitude and amazement the opportunity to freely think about what we truly value and why. This, at least, is something AI cannot do for us. What it is to lead a meaningful life is something we must decide for ourselves.
​- Steven Hales
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.
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Dystopian future city image generated with DreamStudio
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Utopian future city image generated with DreamStudio
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"
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Precarity, Competition, and Innovation: How Economic Systems and Societal Structures Shape Our Future

10/27/2022

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Personal Perspective, Future of Work, Innovation
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The rapid globalization and integration of the economy, including the power of technology to make work performed and done anywhere more accessible have resulted in our 21st Century societies finding themselves at a potentially critical moment in humanity's millennia-long story. 

Our world has shrunk considerably over the past 50 to 75 years. The end of World War II saw with it the birth of a more integrated global economy with capitalism gaining influence as communism waned into the early 1990s. The emergence of China from the 1990s to 2020s also reflects the triumph of global capitalism, albeit state-sponsored capitalism.

​As with any change in how society is structured, there were groups that benefited massively from this shift to a globalized, capitalist (neoliberal) world and those who didn't. One of the main results of this shift was many goods became cheaper to produce and consumer prices, at least in the United States, remained low for decades. 

For nearly 40 years, the average percentage change in consumer prices in the United States barely crossed 5%. In fact, median "inflation" (ie, yearly change in consumer prices) was 2.8% from 1983 to 2021 (we are a far cry from those levels in 2022, though). Compare this to the growth of capital and investment returns over the same time period. The median rate of yearly return for the S&P 500 (a basket of the 500 largest US-based corporations) from the same period, 1983 to 2021 was 12.8%. While this is not perhaps the most elegant economic analysis, I think it demonstrates how much relative value in capital was produced relative to costs passed on to consumers...nearly 10% more per year. 
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Note the axes for the percent change in the S&P 500 Index are nearly 7 times as large as that of the CPI graph above, demonstrating large percentage gains in US stock prices relative to consumer prices, historically, over this time period.
Clearly, the returns to capital relative to the costs born by consumers was the result of companies trading more expensive labor for cheaper means of production. For a time, this bargain seemed "good" for many...prices were kept (arguably) artificially low through low-cost labor. Many workers in more economically developed countries didn't see this shift in economic structure as a problem as it benefited many of their pocketbooks either via high rates of return on capital and/or lower cost goods. Some individuals, especially those working in manufacturing sectors in the United States, Europe, Japan, and other developed countries saw opportunities shrink in favor of increased outsourcing of their work to China or, at least in the past few decades, automation. 
For a time, a global, capitalist, and neoliberal economy seemed to produce more overall prosperity than what came before it. Millions were lifted out of poverty and provided jobs that allowed them to live a life of greater convenience and security. The emergence of China's middle class was the growth engine of the global economy for the past 20-plus years. In a cruel twist of fate, however, the continual pursuit of maximum profit, minimal cost, and "optimization" of a global, capitalist economy may end up resulting in an overall more impoverished world. Globalization produced ever more competition amongst labor markets and the shock of the COVID-19 pandemic illustrated that a complex, global supply chain only works when all its requisite components and inputs are allowed to flow across borders and oceans.  
Competition drives innovation. The market forces that have dominated western economies in the neoliberal area allowed corporations and organizations with more innovative products to increase their profits. In sum, the lives of those using these products also became better. However, those groups that could not innovate and adapt died, resulting in layoffs and loss of entire sectors of our economy. The destructive nature of capitalism is fundamental to its success. There must be winners and losers. 

A bigger philosophical question facing the United States in particular as we approach the end of the first quarter of the 21st Century is whether we will allow the innovative and destructive forces of capitalism to continue to affect our citizens' personal health and wellbeing. Deaths of despair (from suicide and drug overdoses) have risen in the United States over the past 15-20 years despite our overall gross domestic product (GDP) per capita continuing to rise relative to other developed economies. 
The juxtaposition of income inequality and high poverty rates in the US along with overall greater economic growth and productivity of our economy as a whole illustrates that our current form of "US-led, global capitalism" results in big winners and losers. 
​
Some illustrative data from McKinsey's Rethinking the Future of American Capitalism report drive home the point: 
  • American firms rank among the most widely known and the most profitable globally: in economic profit, they make up 38 percent of the top 10. 
  • In the United States, just 6 percent of counties account for two-thirds of GDP output.

​In addition, a variety of data available from inequality.org, sourced from OECD statistics and the Credit Suisse Global Wealth Report highlight the enormous share of wealth concentration in the United States relative to other developed countries.
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The United States has more wealth than any other nation. But America’s top-heavy distribution of wealth leaves typical American adults with far less wealth than their counterparts in other industrial nations.
In exchange for our dynamic and growing "economy" (ie, corporate profits) in the US do so many have to be left behind?
​
What is the ideal balance between creative destruction, economic progress/reinvention, and the stability of our society? When should workers be protected at the potential expense of consumers? Will work as we know it be a thing in the future? And if not, is more time for leisure and creative pursuits for all a good thing? Will humanity fill the free time of a technology-laden future making the world better or worse?  


These are thorny questions and ultimately how things transpire is unpredictable but that does not mean we don't have some agency in shaping the future we want to see. ​
We have constructed a society in the United States where so much of the social safety net has been removed that we may ultimately become less innovative as a society. Who can afford to take the risk of starting a small business or company when they lack affordable access to health insurance or reasonable childcare costs? There is data supporting the notion that innovation is lower in more unequal societies. ​
Innovation also threatens many people's sense of value and contribution to society. As artificial intelligence (AI) becomes more capable at replacing work traditionally performed by humans, even white-collar work, many are left asking how they can contribute to society. The decline in American's confidence in institutions leads one to wonder whether individuals will feel the need to engage with larger societal structures in the future or choose to escape to some version of the metaverse (a la Ready Player One). 
Clearly, this is a time of immense change and uncertainty.
Will we become a less globalized and interconnected world, retreating inwards as societies and people?
Will the speed of automation and change result in many being left behind economically in the new world order?
​Will inequality continue to increase with potentially explosive societal consequences? 

A fundamental set of questions arises: Is our system broken? Can it be reformed? Must it be re-envisioned? Do we have the collective and political will to make real change?
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Is the sun rising or setting on economic progress and opportunity for all as we approach the quarter-point of the 21st Century?
The current structures of our society add further complexity to addressing the problems we face. What is "right" is not always what is popular making it difficult for a democratic country to push forward with changes that may be difficult in the short-term but lead to long-term positive impact. While pursuing my Ph.D. in neurobiology from UNC Chapel Hill, I looked at delay discounting behavior...the tendency for people and animals to discount the future. The future is "worth" less than the present partially because at an individual level the future is uncertain. You may not make it to the future and so why delay consumption now? The YOLO ("you only live once") choices of many young adults reflects the underlying basic instinct of all living things to prioritize the NOW over the LATER. It is in our nature to do this.  
In large part, I think our politicians and leaders have failed to articulate a truly promising view of the future and America's place in it. Rather, "othering" and blaming certain groups is used for political gain while real solutions go undiscussed and our two-party system fosters division and extremism. We have the potential to move closer to being a true melting pot of culture and ideas, welcoming immigrants from across the world who seek to better their futures and our country as a whole by leveraging American Capitalism and the innovative ecosystems it can foster.

​If we don't find a way to strike the right balance between growth at any cost and compassion for all people within our society, though, we could lay the seeds for the destruction of the future we all want to see. 
More from the blog:
  • The End of Work as We Know It: How an Increasingly Automated World Will Change Everything
  • The Challenges of Being an International Researcher: Implications for Advanced Degree Labor Markets
    • Part 1
    • Part 2​
For Further Reading:
  • What exactly is neoliberalism?
  • Book: Capital in the Twenty-First Century
    • See also the documentary on the topic
  • Rethinking the future of American capitalism (from McKinsey)
  • Inequality: A persisting challenge and its implications (from McKinsey)
  • The social contract in the 21st century: Outcomes so far for workers, consumers, and savers in advanced economies (from McKinsey)
  • Book: The Power of Creative Destruction: Economic Upheaval and the Wealth of Nations
  • Book: US vs. Them: The Failure of Globalism
  • Book: Six Faces of Globalization: Who Wins, Who Loses, and Why It Matters
    • More on this concept from one of the book's authors, Anthea Roberts on her personal website
    • Who wins and who loses from globalization? There are (at least) six answers (excerpt from the Book)
    • The Corporate Power Narrative: How Corporations Benefit from Economic Globalization (excerpt from the Book)
  • Book: Deaths of Despair and the Future of Capitalism 
  • America's crisis of despair: A federal task force for economic recovery and societal well-being
  • Book: Forward: Notes on the Future of Our Democracy 
  • Relevant political reads from The Atlantic:
    • ​How the U.K. Became One of the Poorest Countries in Western Europe
      • ​A cautionary tale?
    • The Wreckage of Neoliberalism
      • The postwar neoliberal economic project is nearing its end. The question is who will write the last chapter, the Democrats or the totalitarians?
Sites Worth Exploring:
  • INEQUALITY.ORG (United States and global data)
  • realtimeinequality.org (United States data)
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Reimagining the Postdoctoral Experience

6/30/2022

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Scientific Workforce, Future of Work
The views expressed here are my own and do not necessarily reflect those held by Virginia Tech, the National Postdoctoral Association, or the Graduate Career Consortium.
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What is a postdoc? What is it for?

This question is a persistent one for many working within and outside academia. 
Working in this space, we often label postdoctoral scholars as trainees and employees, which is a tricky line to walk.

Freshly removed from their Ph.D. training, many postdocs struggle with defining themselves. Breaking out of the mindset of student to budding professional is not easy. As institutions, we should reflect on how the postdoctoral experience is value-add from graduate school training. How do we ensure postdocs are learning and growing and not simply "doing work" related to a faculty member's research? The answers to these questions are important as the higher education sector struggles with recruiting and retaining talent in a tight labor market. 
A recent piece in Science highlights that many faculty members have struggled recruiting postdoctoral researchers over the past year or so, which is most likely related to a strong job market and reconsideration of life priorities as a result of the COVID-19 pandemic. It also may indicate that Ph.D. students are more carefully considering what role a postdoctoral position plays in their overall career trajectory. I think individuals more carefully considering whether a postdoctoral position is necessary for their career development and growth is a good thing. Also, institutions could do more to illuminate the value of postdoc training by reimagining what it can be.  
It is important to remember that  both graduate students and postdoctoral researchers contribute cutting edge knowledge and discoveries that drive innovation to improve our world. Furthermore, postdoctoral researchers are more able to devote time and effort to research and discovery given they no longer have course or degree requirements to meet. But are we allowing them to fully realize their potential in our current model?

It is my opinion that our institutions must ensure postdoctoral scholars not only have the tools and resources to do amazing research and scholarship at their institutions but are developed as full people and community members. We should work to assist postdocs in discovering how their skills, interests, and values can be put to use to serve their campuses and local communities and, ultimately, the world. 
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Value of team science and community engagement
Part of the reason postdocs are overlooked on their campus is that they are often isolated from the larger institutional community as they perform intensive research and scholarship. There was a time when devotion to the development of this deep expertise in a scholarly area was sufficient to ensure success in an academic career. Those times are over. Team science and scholarship are essential for academics to thrive in the 21st Century and postdocs who develop these skills will be more effective faculty researchers.

In addition, a singular devotion to research and scholastic productivity can lead to a situation where a postdoctoral researcher ties their worth to their work. This dynamic stresses the mental health and wellbeing of some of our most well educated and trained researchers and can lead them to abandoning promising careers. One way to improve this situation is to provide outlets for postdocs to contribute to causes beyond their research and scholarship. Volunteering in their local postdoctoral association, the National Postdoctoral Association, and local community provides a variety of benefits including:
  • Allowing them to hone key transferable skills including communication, teamwork, project planning, and management 
  • Facilitating social interactions and community building
  • Allowing for postdocs to contribute meaningfully to something bigger than themselves
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Increase visibility of postdocs and their value to their institutions & communities
​Postdocs can (and do) provide value to their campus community beyond their research endeavors. We should work to aid institutions in better integrating postdocs into many of their teaching and innovation efforts including:
  • Provide mentoring training to postdocs to allow them to more effectively mentor undergraduate and graduate students in their research groups
    • Mentoring training will also prepare postdocs to effectively lead and manage teams in their post-postdoc careers (faculty or otherwise)
  • Encourage opportunities for postdocs to build and practice pedagogical and teaching skills
    • Provide access to teaching and pedagogical training to postdocs which could then allow them to contribute to campus needs in a variety of ways:
      • Postdocs could serve in a guest lecture pool that a university maintains to give them small teaching experiences
      • Encourage postdocs to lead workshops and trainings on techniques and tools they are experts in to their campus communities 
        • See NC State’s Peer Scholars Program as an example
        • Ideally, some form of financial compensation would be available for the above work
  • Provide postdocs access to information and training in intellectual property, technology transfer and commercialization, and entrepreneurship to encourage and empower them to shepherd key innovative research taking place in our universities and research centers to ultimately produce products and services that can benefit society
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Postdoc positions as a bridge between academic research & the world of work
While a traditional postdoctoral position had the goal of preparing Ph.D.s for faculty positions, they could also morph in the 21st Century to serve as a bridge between academic training and careers beyond faculty.
  • Many companies require the highly technical skills that Ph.D.s have developed in their training
  • However, acclimating Ph.D.s to the world of corporate work and the language and procedures of business is a challenge
  • Why couldn’t the postdoc also serve as a way for companies to access Ph.D. talent without necessarily committing them to a permanent position?
    • Companies can test-drive candidates while giving them access to useful experiences that diversify their resumes through collaborative internship opportunities
  • In addition, there may be a place for postdocs to serve as a nexus between academic research and commercialization opportunities
    • A large bottleneck in the commercialization of academic research is that the principal investigators responsible for leading research groups often do not have the time to devote to liaising with potential companies to explore licensing their technology
      • Postdocs could serve as a useful intermediary between academic research and companies to help ensure a greater number of innovative research developments can be translated into real-world solutions
      • In the process, postdocs gain a greater understanding of the language of the business world, intellectual property, and technology commercialization 
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Practical Considerations 
One big issue that would emerge from a reimagining of the postdoctoral experience is how to apportion postdocs’ time devoted to research and scholarly efforts, especially those supported on a faculty member’s research grant (as the majority of postdocs are), versus the additional activities describe above.

While the United States government’s Office of Management and Budget has issued guidance on the “dual role” of student and postdoctoral researchers emphasizing that graduate students and postdocs supported on federal grants are both trainees and employees and expected to be actively engaged in their training and career development, nowhere is an expected distribution of time devoted to training and career development versus research work and activities specified. There is still a sense from many faculty whose research grants support postdocs that they are paying postdocs to do the work and not engage in “extracurricular” activities and that those should occur outside “business hours”. International postdocs whose visas are tied to their research roles may be especially reluctant to allocate time to career and professional development activities if their faculty supervisor does not encourage their engagement in them. The concerns of faculty could be minimized if they aren’t paying a postdoc when they are engaging in activities outside their research and scholarly responsibilities.      

Thus, steps may need to be taken by institutions to effectively distribute resources and funds to support the proposed broader set of postdoc activities mentioned above. I think it is in our best interest to do so. Universities will need to think hard about investing in postdoc compensation, perhaps covering 20-25% of a postdoc’s costs with the rest coming from faculty member’s research grants and funds. It would also be reasonable to assume that if an institution is investing resources in supporting postdocs’ salaries to allow them to engage in a wider range of professional development activities that they would come to see postdocs as an asset to the institution. As a result, perhaps a greater effort would be made to provide a more comprehensive set of resources for postdocs who the university is now, literally, invested in. Institutions with skin in the game might also begin to reflect on the purpose of postdocs, resulting in a needed discussion on whether training is indeed occurring in some roles or whether they would be better classified as research staff.

​The concept of research staff tracks for Ph.D.s within universities is beyond the scope of this post but could be a means of retaining skilled talent who don’t necessarily want the responsibilities of a principal investigator or lab leader at a university. And while universities and other postdoctoral training institutions often balk at "investing" in a population who will ultimately leave (as the position is meant to be a temporary one), they could benefit from postdoctoral scholars more engaged in service to the university through teaching, outreach, and commercialization efforts. This setup could be a win-win for postdocs with a desire to learn new skills and obtain diverse work experiences and institutions experiencing staffing shortages.   
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Parting Thoughts
​In closing, it is my personal belief that the path forward is to ensure the postdoctoral period is a time of broad training for Ph.D. researchers. If we can equip them with both technical, scholarly, and transferable skills, they will be able to make an impact in the world. Furthermore, providing postdocs the opportunity to engage with their campus community through service will enrich their experience and lives. In addition, this model may provide needed personnel relief for universities that have struggled over the past few years retaining talent. While postdocs receive valuable experiences in teaching, technology commercialization, or project management, our universities benefit from their work in these areas. Pathways for skilled researchers to remain at universities in professionalized research (or staff) tracks may also be appropriate to retain talented postdocs with a desire to stay at an institution but not become tenure-track faculty. 

Only by being open to a new way of doing things in postdoctoral training and career development can we truly move institutions forward and, in the process, provide a means for them to leverage Ph.D. talent in ways that enhance their research, teaching, service, and outreach missions. 
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Post-Ph.D. Career Plans: Consider the Possibilities

3/7/2020

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Ph.D. Career Trends
The post originally appeared on PassioInventa, a site run by graduate students to serve as a platform for science communication. 
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Many people assume Ph.D.-trained individuals work in two predominant areas: academia or industry. Most professors have Ph.D.s, and academic careers are  considered to be the “default” or even preferred path during one’s graduate training.
The other major career bucket Ph.D.s fall into after their training is industry. What do we mean by “industry”, though? Many assume an industry Ph.D. works in pharmaceutical development or some other research and development (R&D) role, and some, indeed, do. However, there are so many additional roles Ph.D.s can fill in industry as well as in government, nonprofits, and academia that don’t fall into the neat buckets of academic or industry scientist.
What do Ph.D.s do for work? Let’s look at the data.
A wealth of career data for Ph.D. recipients is collected by the National Science Foundation (NSF) in its
Survey of Earned Doctorates (SED) and Survey of Doctorate Recipients (SDR). The SED focuses on recent Ph.D. graduates each year (Table 1) while the SDR captures employment information of individuals with Ph.D.s in science, engineering, or health fields, regardless of when they received their degree (Table 2).
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Table 1: Survey of Earned Doctorates (SED) data on primary work role for 2018 Ph.D. graduates in the life sciences, physical/earth sciences, and engineering. R&D, Research & Development
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Table 2: Survey of Doctoral Recipients (SDR) showing primary work role of individuals with life sciences, physical/earth sciences, or engineering degrees in 2017. R&D, Research & Development
The data collected by the NSF demonstrate that anywhere from 34.1% to 37.3% of science/engineering doctorates ultimately perform work beyond R&D and teaching (Table 2, Something Else column). That number might surprise current graduate students and postdoctoral trainees who often consider their career options limited.  
Ph.D. employment trends are changing: The elephant in the room 
A great challenge in graduate education and career/professional development is ensuring Ph.D.-trained researchers understand that the “traditional path” of securing a faculty position is becoming more difficult to follow. This trend was  summed up well by Schillebeeckx et al 2013 (reproduced below), who show that the cumulative number of Ph.D.s awarded in Science & Engineering fields has grown rapidly compared to available faculty positions over the past few decades.
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This  chart includes data collected through 2011; the startling trend has unfortunately continued. More recent data can be accessed from the SDR & SED on employment trends for Ph.D.-trained scientists and these data continue to show the decline in the percentage of Ph.D.s working in tenure-track faculty positions. The trend is most apparent in the SDR data where employment in academic positions is broken down by tenured faculty, those on the tenure track, and those in positions not eligible for tenure. In addition, the data is categorized by those who received their Ph.D.s <10 years from the survey (representing early career researchers and postdocs) and those 10 or more years post-Ph.D.. The change in the academic employment landscape for these recent Ph.D. graduates (Table 3) illustrates the radical shift occurring in Ph.D. employment at 4-year educational institutions.
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Table 3: Percentage change in recent (<10 years from degree) Ph.D.s employment at 4-year educational institutions in the United States from 2010 to 2017, calculated from NSF SDR data.
Growth in non-tenure track employment among science Ph.D.s
Where are these Ph.D.-trained scientists going? While some are moving into career fields outside of academia -- in fact the 2017 SED data showed private sector employment of science/engineering Ph.D.s (42%) was
nearly on par with educational institution employment (43%) -- many are working in non-tenure track positions that could include lecturers, adjunct faculty, research faculty, or postdoctoral positions. Table 3, above, shows the 2-3x growth in these non-tenure track positions in a period of just 7 years.
​Further examination of the 2017 data showed an astounding 17.1% (~1 in 5) of those with life science Ph.D.s employed at 4-year academic institutions were postdocs.
What is a postdoc and should I pursue one? 
"A postdoctoral scholar (postdoc) is an individual holding a doctoral degree who is engaged in a temporary period of mentored research and/or scholarly training for the purpose of acquiring the professional skills needed to pursue a career path of his or her choosing."
-National Postdoctoral Association 
While completing a postdoc has been a natural step toward securing a faculty career, it has also, unfortunately, become a holding place for Ph.D.s who have not been able to secure faculty employment. In addition, remaining a postdoc for too long may have serious effects on one’s lifetime earnings potential. In fact, many Ph.D.-trained individuals should probably not pursue a postdoc but a lack of information on career opportunities for Ph.D.-holders leaves many to default to the postdoc path.
My own story navigating the academic career path
I was one of those individuals on this default postdoc path. I had a great graduate school experience at UNC Chapel Hill and felt encouraged to stay in academia and pursue a postdoc with the goal of learning a new scientific technique (PET imaging of the dopamine system). My ultimate goal was to land a tenure-track faculty job.
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Completing my graduate training in the lab of a recently-hired faculty member certainly showed me that landing the faculty job is only step one on the path to the idealized tenured professor position. An equally difficult step is being productive to obtain tenure. A faculty member who obtains tenure needs to publish papers, secure grant funding, mentor effectively, perform service for one’s home department, and often teach. 

While the public sees a faculty job as pretty cushy -- and maybe after securing tenure it gets a bit more cushy (or at least secure in terms of your salary) -- the path to obtaining that tenured position is an arduous and tenuous one. There are so many places where one can fall off this pathway of postdoc -> assistant professor (on tenure-track) -> tenured faculty.

​Collaborative work from the
Future_PI Slack group which I have been involved with shows that every year, very qualified individuals who apply for assistant professorships don’t succeed. 

The average person (and most family members of graduate students) really has no idea the challenges Ph.D.s face in launching their careers. I know I was certainly not the first person whose parents inquired when I would be “done” with training and get a “real job”. They meant well but, like many people, assumed once someone has a Ph.D., aren’t they “done” and on the quick path to fortune?
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Acknowledging my faculty career doubts and discovering alternative career paths during my postdoc 
I spent 4.5 years as a postdoc at Vanderbilt University and it was a really wonderful time. I felt I grew as a person,
contributed important work to my field of neuroscience, and gained leadership experience in the Vanderbilt Postdoctoral Association. And while I went deep down the path toward obtaining a faculty position (even getting an onsite interview back in Spring 2018), in the back of my mind I had doubts about being a faculty member; that path just didn’t feel right. Having access to career/professional development programming at Vanderbilt helped me learn about other career paths for Ph.D.s.

I now work in career and professional development helping current graduate students and postdocs at North Carolina State University. 
You can read more about my personal career exploration journey and transition to postdoc affairs in my series of NIH BEST blog posts.
Career exploration is where it all begins
Part of the search for a post-Ph.D. or post-postdoc career is a search for yourself. This sounds kind of intimidating - and it is. But trust me when I tell you people like me do make it through a challenging career search, and along the way they often discover what is most important to their wellbeing and happiness. Seems like a pretty nice outcome after navigating the hard, twisty road to a career.

For a deeper dive: Explore the NSF data referenced in this article

See my previous Blog pieces on career exploration:
Start here
career exploration 101

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The End of Work as We Know It: How an Increasingly Automated World Will Change Everything

12/16/2019

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Career & Professional Development, Opinion
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Updates, February 2021:
​I encourage anyone interested in the future of workforce development and training to read this excellent article published in Forbes: 
Human Capital Era Reality: The Skills Gap May Never Close

For other relevant readings on the future of work, see:
Future of Work: Insights for 2021 and Beyond (Milken Institute)
The Future of Work After COVID-19 (McKinsey Global Institute) 
​Preparing for the Future of Work (World Economic Forum)
World Economic Forum's Future of Jobs Report 2020

In a few short weeks we will be entering a new decade.

What will the 2020s hold? Technological advances continue to take shape at a blistering pace and will have effects on nearly all aspects of our lives. While most of these tech advances will be a clear benefit (improved healthcare, faster connectivity with 5G wireless, and greater access to online learning), others offer a potentially existential challenge to something most of us do for more than a third of our lives: work.  

Work in the Age of AI
The nature of work is changing rapidly. Automation and artificial intelligence (AI) are allowing machines and computer programs to take on an extraordinary variety of tasks.
We think of this as a blue-collar issue with robots now doing most of the assembly at automobile plants across the world and autonomous vehicles coming to take truckers jobs soon. The truth is, though, very few jobs are safe from automation as many jobs are quite routine and skills-based.

Any job requiring technical skill alone may eventually be subsumed by advances in AI. This leads to the important question of how does one prepare for this sea change? How can you make yourself un-replaceable by a machine?
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A 2017 McKinsey Global institute study concluded up to 800 million workers worldwide could lose their jobs to automation by 2030.

Workforce Transitions in a Time of Automation (McKinsey, Dec 2017)
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What Skills Will Be Valued in Future Work?
While it seems logical to assume that increases in AI would necessitate increased training in technical skills like computer programming, coding, engineering, or other scientific fields, the fact of the matter is that those technical skills themselves may be unsafe from the evolving capability of our machines.
Specifically, a report by the Brookings Institute where job descriptions were compared against AI-related-patents (see paper by Michael Webb at Stanford University for empirical details) found that white collar, data-intensive jobs in business, technology, engineering, and science are at greatest risk of being impacted by AI. The report quantified impact as having job duties that could be subsumed by coming AI advances. This doesn't mean AI would replace the job completely...in fact, AI may just supplement work in fields such as finance and scientific research. What is clear, though, is that only being good at a skill or technique that eventually can be automated is NOT a winning strategy. 


​"AI exposure will likely lower wages and lead to job replacement if human workers can no longer bring "extra value" that AI can't."
- Mark Muro, Senior Fellow & Lead Author of the Brookings report
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Transferable, Human-Centered Skills are Irreplaceable (for now)
What will be in demand for the foreseeable future are transferable skills. These types of skills aren't technical but rather refer to intra- and inter-personal skills that we use to get our work done efficiently, by ourselves or with others.
​
LinkedIn found these 5 transferable skills to be most in demand in 2019 (based on job postings on the platform):
5. Time Management
4. Adaptability
3. Collaboration
2. Persuasion
1. Creativity
In addition, as more and more employees become tech-savvy, backgrounds that give employees perspective — historical, global, or otherwise — will become increasingly valuable. We will need to increasingly think about how our machines and interfaces are designed to interact with humans.

​Currently, machines cannot think like human beings. The AI we have today is so-called "narrow AI,” performing objective functions using data-trained models. The AI from science fiction movies where machines have human-like intelligence, so-called "artificial general intelligence," is far from a reality and may never be achieved. So, we will need people to serve as the interpretational bridge between AI and society and back again...to insert humanity into our machines and their decisions.
  
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Technical Training is NOT Enough:
The Role of Critical Thinking, Problem Solving, Data Synthesis, & Presentation Skills 

There has been an increased emphasis and interest in STEM (Science, Technology, Engineering, & Mathematics) education to prepare the next generation for a new age of work. Colleges, particularly technical schools and community colleges, have invested heavily in career and technical education that seeks to broaden technical skills currently in demand (coding, software engineering, etc...). Ironically, though, being trained in the liberal arts and humanities may be more useful in the age of AI. In addition, there is data suggesting a surplus of STEM majors in some fields (see also this piece from The Atlantic). 

It won't be so much our technical skills that differentiate us in the 21st Century economy. Rather, being able to think critically, synthesize information, present arguments persuasively, and work effectively with others will be increasingly valued. 
Anyone working in the sciences knows that our knowledge and tools change fast. So, it may not be surprising to consider the skills we value now in coding, data manipulation, and analysis may not be what is needed 20 or even 10 years from now. 
"It is not only what you know but how you learn that will set you apart."
- Thomas Friedman, author of The World is Flat: A Brief History of the Twenty-first Century
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Graduate Students & Postdocs Have the Skills Needed for the 21st Century Economy 
Having the skills to quickly dissect a problem, synthesize and interpret data, and clearly present insights and recommendations from your work are incredibly valuable. Luckily, if you have been pursuing a graduate degree or postdoctoral work, you have experience in all these areas. Each day you are working to troubleshoot problems, synthesize your data with what is already known, and form coherent narratives around your findings. You are uniquely poised to make sense of the flood of data that is and will be produced and stored from the countless scientific publications, device interactions, and web searches that occur each day. 
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Even the hot career field of data science is focused heavily on communicating insights from analyses. This skill may become even more critical as computers takeover the work of data preparation and analysis, leaving the humans to extract insights from the work. 
​
Ph.D.-trained scientists are uniquely poised to be the data interpreters we will need in the 21st Century. 
How to Hone & Leverage Your Transferable Skills Into Meaningful Work 
A changing world demands individuals who can change with it. Flexibility and the ability the learn and adapt to new technology will be crucial. Scientists possess these and other transferable skills but need to more effectively hone and communicate them to potential employers.
​In addition, current graduate students and postdocs must avoid becoming so focused in one domain or technique that they don't develop the transferable skills needed to succeed in the 21st Century economy. 
How can current trainees practice and perfect their transferable skills? 
Develop Teamwork & Leadership Skills
Taking leadership roles or volunteering in organizations that you are passionate about (including graduate student and postdoc associations) allows you to give back to your community while also honing your teamwork and leadership skills (for example, see). You can look to get involved with local or national organizations or local chapters of national organizations, potentially in research or career areas that interest you. 
​ 
Volunteering within an organization while continuing in your current role will also force you to improve your time and project management skills as you seek to fulfill your many obligations. In addition, working with others in these organizations, especially those from different backgrounds than yours, will teach you the importance of effective communication skills (listening, synthesizing, presenting), leadership, and consensus building to achieving success. 
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Check out Volunteer Match for community volunteering opportunities. ​
Communication Skills
You should also seek out opportunities to practice and demonstrate your communication skills. Join Toastmaters to practice your public presentation skills or volunteer to deliver a talk to a general audience (local science cafes/clubs are a great venue). You can also start posting articles on the web to demonstrate your written communication skills (LinkedIn has a great self-publication feature). Showing you can speak to a general audience and not just academics is crucial. Your future coworkers and customers will have a variety of backgrounds and speaking to them in an accessible way will increase the rapport you can build with them.  ​
Final Thoughts
While ​the future of work in the age of automation may seem scary, there is the real possibility that increased efficiencies will free us to do tasks that are mentally stimulating and personally rewarding. Instead of slaving over data we will be able to spend our time thinking about how it can be used to better the human condition. We will be able to spend more time interacting with one another instead of at our screens doing the menial tasks that often accompany knowledge-based work. 
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A more automated and efficient world will provide us more time to do what we enjoy and give back to others: to do meaningful work. By freeing us of routine, tedious tasks, AI also has the ability to unlock the vast untapped potential in so many of us...to allow us to pursue work and activities that are not motivated so much by their utility and profitability (as the machines will do much of that) as by their ability to bring happiness to our and others lives.
That is certainly a future worth aspiring towards.   
Further Reading
AI & Work

Where Machines Could Replace Humans - and where they can't (yet)

What jobs are affected by AI? Better-paid, better-educated workers face the most exposure

Is Technology About to Decimate White-Collar Work?

When Will AI Exceed Human Performance? Evidence from AI Experts

​
In the Age of AI (PBS Frontline documentary)

Human Flourishing in the AI Age - We Need a New Story


Education & the 21st Century Labor Market 
The Myth of the Science and Engineering Shortage
​

STEM Crisis of STEM Surplus? Yes & Yes

A Humanities Degree is Worth Much More Than You Realize

The Growing Importance of Social Skills in the Labor Market

You Can Do Anything: The Surprising Power of a "Useless" Liberal Arts Education (book)

The Future of Work
​Meaningful Work: Viktor Frankl's Legacy for the 21st Century (book)

Life's Great Question: Discover How You Contribute to the World (book)

The Globotics Upheaval: Globalization, Robotics, & the Future of Work (book)

MIT Initiative on the Digital Economy 
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    A neuroscientist by training, I now work to improve the career readiness of graduate students and postdoctoral scholars.

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