Scientist Deus: Plan Your Career as a Scientist in the Age of AI
How can you plan your career as a scientist while technology is changing what it means to be a scientist? What will scientists even do in the future? As the lines between technology and biology blur, computers will undoubtedly relieve scientists of some of their duties. Will you be empowered by sophisticated artificial intelligences or stripped of your intellectual identity? Although Yuval Noah Harari’s Homo Deus isn’t specifically about scientists, I highly recommend reading it and constantly framing its thought-provoking questions and scenarios from the perspective of a scientist. Think about what the future might look like and consider how you can ride the wave of artificial intelligence rather than being drowned by it.
Staying ahead of the AI wave
Harari’s predictions about the future emphasize the importance of recognizing and participating in emerging trends. Specifically, he focuses on how advancements in technology, biotechnology, and artificial intelligence will redefine what it means to be human. For scientists, riding these waves will crucial to remain relevant. This will require a serious commitment to continuous learning and adaptability.
Scientific knowledge is expanding at a breakneck pace. New discoveries and innovations are constantly emerging, and scientists must be proactive in keeping up with these changes or risk being left behind. But there are only so many hours in a day and it’s easy to get buried under a pile of papers you fully intend to read. Instead of trying to keep up by simply working harder, figure out how to empower and amplify yourself with AI. That will require learning new skills like programming, prompt engineering, machine learning, mathematical modeling, or even simply adjusting your workflows to include more digital tools.
Your next education may involve attending conferences, enrolling in courses, or–more likely–engaging in online self-study. Whichever learning path you choose, you must ensure that you are well-equipped to tackle the new challenges at the scientific frontier and to seize opportunities as they arise. Lifelong learning is not a new concept, but it is one of the most important skills you can develop as a scientist.
The Scientist Algorithm
One of the central themes in “Homo Deus” is the power of data and algorithms. Harari argues that computer algorithms aren’t really any different from the algorithms that govern life and nature. As life and consciousness converge with digital systems, the line between scientists and computers will blur. In the few short years since the writing of “Homo Deus,” deep learning transformer models have made enormous leaps in generative AI and quadriplegics are using brain implants to control computers with their minds. These advances give some credence to Harari’s futuristic extrapolations. You’ll start to appreciate how difficult it is becoming to differentiate between consciousness and intelligence and algorithms and the data (experiences) used to to train a model. I walked away from this book seriously considering Harari’s thesis that consciousness and intelligence have become uncoupled.
The consequences of this layered blurring on the philosophical underpinnings of humanism are profound, but we’ll steer away from that minefield for the moment. Instead, let’s focus on how the professional identity of scientists will evolve in the coming years amidst this dynamic.
Scientists generate data
As any cynical graduate student knows, humans have value as set of dexterous hands. In that context, a scientist’s output can in some ways be limited by their physical ability to manipulate the tools of their trade. Analogously, a mechanic is capable of assembling a car using their hands and tools. That mechanic could use their expertise to teach others how to repeat the same process, allowing their shop to scale up its production as a linear function of the number of workers employed. But by combining their expertise with new technologies, the mechanic could create a new process or factory capable of exponentially increasing the rate of production. While this analogy is obviously from the early 20th century, in many ways modern scientists similarly limit themselves by identifying as master craftsmen.
Think about the explosive acceleration in the rate of genetic data production catalyzed by next generation sequencing methods. Consider how AI vision models could help you analyze hundreds or thousands of times more micrographs. What will the next leaps forward be? How would you allocate your time most productively if you had humanoid robots doing your bidding in the lab 24 hours a day seven days a week? That’s not going to happen any time soon, but the rest of your career will follow that trajectory. Embrace the inevitable trend: figure out how to generate orders of magnitude more data with robotics, new technology, and clever experimental design.
Scientists analyze data
But do you know who analyzes data better than humans? Computers. Computers can analyze enormous datasets and evaluate the significance of hundreds of variables without your human bias. We’re already there. (You just need to feed the computer a lot of data. See above.) Some basic programming and data analytics skills are all that is needed to take advantage of this incredible capability. Yet, computers currently lag far behind humans at interpreting analyses by themselves. That will likely persist for at least a while. But even today, AI systems can make a scientist better at interpreting results. Retrieval augmented generation (RAG) and knowledge graphs can organize the increasingly unmanageable volume of scientific publications and find interesting connections that might be worth probing experimentally.
Future scientists will be empowered by technology
You must learn to incorporate AI tools into your work as a scientist. Learn to harness these great powers to generate, analyze, and interpret data in ways that were unimaginable to Newton, Curie, Watson, or any of the scientific heroes upon whose shoulders we stand. As science and technology hurdle forward at an increasing rate, you will not make it to the end of your career before these tools transform what it means to be a scientist. So either adapt or you’ll preclude yourself from the super-scientist echelon that dominates science. (If you find this line of thinking inflammatory and over-the-top, at least acknowledge that you job prospects will be significantly greater if you’re fluent in data analytics and AI methodologies.)
The Transition from Homo Sapiens to Homo Deus
Harari explores the idea of humans evolving into “Homo Deus,” beings with enhanced abilities achieved through technological and biological advancements. This concept has profound implications for scientific research and innovation. In fact, Harari primarily blames scientists (not technologists) for demystifying the biological mechanisms that make humans human. He says that scientists have shattered the sanctity of consciousness which seems to be just an emergent phenomenon resulting from explainable electrochemical processes formed through Darwinian evolution. As scientists push the boundaries of what is possible, they must also consider the ethical implications of their work.
Responsible innovation should be a core principle for scientists. This means not only pursuing groundbreaking research but also considering its potential impact on society and the environment. As we design increasingly sophisticated and transformative therapies, we are already seeing the spillover from curing those in need to enhancing those without any pathology.
In one example, the wealthy are paying out-of-pocket for Mounjaro and Ozempic to drop a few pounds while some with legitimate medical needs are unable to pay for the incredibly effective medication. In another, it now seems likely that–in addition to truly transforming the lives of the paralyzed–implanted brain computer interface devices will in the not-to-distant future create a class of superhumans. Unburdened by the extra milliseconds it takes for an electrical impulse to travel from the brain down to the fingers, these new superhumans will dominate Esports competitions (as the most benign of potential examples).
As scientists, we enable these incredible feats and should bear some responsibility for the inevitable outcomes of transcending traditional human limitations.
The Importance of Interdisciplinary Knowledge
Harari emphasizes the convergence of different fields, such as biology, technology, and economics, in shaping the future. It should be no secret to scientists that breakthroughs often happen at the unexpected, unexplored interfaces between distant fields. There are two practical pieces of career advice that follow from this point: 1. network widely and 2. study and think broadly.
Network widely
You won’t forge these unexpected connections without talking to people outside your field of expertise. As a pleasant side effect, a broad network can do wonders for your career advancement prospects, independent from the actual results you produce.
Study and think broadly
It takes a lot less effort for a great biologist to develop basic machine learning skills than to become the absolute leader of their field. So allow yourself to scatter small investments in many orthogonal fields. You may just hit it big on these small bets, making a truly interdisciplinary discovery. Put differently, the expected marginal benefit of an investment of 1000 hours towards learning some aspect of a different field will undoubtedly be higher than an extra 1000 hours invested in your primary niche (where you’ve already invested tens of thousands of hours).
Building an interdisciplinary career
But the pursuit of scientific breakthroughs is not the only reason to pursue interdisciplinary projects. Building your interdisciplinary muscles will enhance your career in several ways.
- Experience across fields prepares scientists for leadership positions (e.g. department chair or dean) which inevitably require managing groups with diverse perspectives
- Crafting a multidisciplinary specialty by mixing and matching fields can allow you to own a particular niche. You can carve out a particular space as your own by combining three disparate fields. You’ll truly be a one-of-a-kind unicorn.
- Broader experiences and skill sets act as a buffer against future uncertainties. As problems, fields, and technical approaches evolve, it doesn’t hurt to be flexible. Put positively, as new problems emerge you’ll have the flexibility to respond and tackle those new problems. In fact, this point is so important, let’s devote a whole section to exploring it.
Preparing for an Uncertain Future
Harari’s perspective on the uncertainties of the future is particularly relevant for scientists. As the pace of scientific progress and technological change continues to accelerate, no one knows where we’ll be in a few short years. It’s almost certain that we’ll each have multiple careers. We’ll have no choice but to adapt and evolve. In the face of constant change, the most important areas for personal development will be resilience and strategic foresight.
Resilience and a growth mindset
Resilience Is the ability to adapt to changing circumstances and overcome challenges. Scientists do this everyday in the lab, overcoming and circumventing the curve balls that nature and experiments throw at them. However, many scientists struggle with aspects of interpersonal resilience. If your advisor or boss fails to live up to your platonic ideal of a mentor, don’t wallow in the negative emotions at the expense of your career. Use it as an opportunity to develop a different aspect of your resilience. This is an example of having a growth mindset.
A growth mindset is the belief that abilities and intelligence can be developed through dedication and hard work. Everyone can believe this in the good times. But steadfastly maintaining this perspective in the face of adversity and at emotional low points is the mark of a great growth mindset. Any interpersonal problem a scientist confronts in their professional life can be framed in the context of a growth mindset. For example, if you feel that your mentor isn’t supportive, you can persevere and succeed by developing a strong network and practice your negotiation and mediation skills. You will have grown multiple skill sets while solving your primary problem. These skills and your learned-through-practice resilience will serve you well throughout your career–especially in the uncertain future for which there is no specific training manual.
Strategic thinking and foresight
Strategic foresight involves anticipating future trends and preparing for potential scenarios. At a macro level, you should regularly assess the landscape of your field, identify emerging trends, and consider how these might impact your future work. At more of a micro level, you should be thinking probabilistically about the expected benefit you’ll gain from diving into some project or going the extra mile on an experiment. Weigh that against the probabilistic expected cost to you in terms of opportunities foregone which may include personal happiness, financial security, and disappointing your boss.
Strategic foresight is the actionable output of myriad analyses of these types—spanning multiple time horizons and every aspect of your personal and professional life. Whether you’re trying to get promoted as quickly as possible, maximize your publication record, or achieve an optimal work life balance, developing your strategic thinking skills will serve you well in any version of the future.
Call to Action
Take an active approach to your career:
- Anticipate trends and harness their momentum
- Embrace the power of artificial intelligence to make you a better scientist
- Create an interdisciplinary niche for yourself
- Develop a growth mindset to capture value from adversity
These goals require consistent reflection and focused strategic thinking. Commit the time and don’t let these important activities slip because of ordinary stressors.
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