Dear Friends,
On July 25th, 2024, Nature published an interesting article titled "Scientists Need More Time to Think." While emails and instant messaging tools are essential to research, they also serve as major distractions. The article references a book by computer scientist Cal Newport, Slow Productivity, which discusses how science is becoming less disruptive despite an increase in the number of papers and grants. The paper suggests that knowledge workers need to slow down and spend more time thinking! It poses an important question: “What is the impact of lost concentration time on science—not just on the structure and process of science, but also on the content and quality of research?”
Ideally, a progressive academic institution should wisely identify and categorize faculty into four roles: Impactful Teachers (for insightful teaching), Deep Researchers (for disruptive ideas), Able Administrators (for effective management of limited resources), and Smart Mentors (for personalized advice and support based on students' socio-physical and psychological needs). There is no hierarchy among these categories; all are equally important in the age of AI-powered education.
We have access to excellent YouTube content that can replace a mediocre teacher. Tools like Scite_, a powerful research tool designed to assist scholars and researchers with enhanced literature reviews, are becoming essential. Writing assistants like Jenny.ai, Grammarly, and Jasper are increasing the scientific productivity of researchers.
Breakthrough unicorn startup Sakana AI from Japan has created the first AI Scientist. This AI can generate an idea and develop it into a full paper at a cost of approximately $15 per paper. The AI Scientist can perform idea generation, literature search, experiment planning, experiment iterations, figure generation, manuscript writing, and reviewing to produce insightful papers. Can you imagine how Sakana AI Scientist intelligently wrote a paper? https://sakana.ai/.../adaptive_dual_scale_denoising.pdf. This 11-page scientific manuscript, written entirely by AI, is formatted like a standard machine learning conference submission, complete with visualizations and all standard sections. The AI's performance is on par with that of an early-stage ML researcher. Thus, a mediocre researcher is also replaceable. A year's work for a researcher can now be done in minutes, allowing the generation of hundreds of medium-quality papers in a week.
AI mentoring tools already offer precise matching, data-driven insights, 24/7 availability, and cost-effectiveness. Hence, a mediocre mentor is also replaceable.
In such a scenario, unless an individual self-assesses where they fit among these four roles (Teacher, Researcher, Administrator, and Mentor), masters that area, and performs beyond mediocrity, their survival in the AI-matured phase is questionable.
That being said, the whole world is in flux right now. Universities, researchers, funding agencies, students, teachers, and parents are all navigating a complex and ever-changing environment. It's hard to determine what will work and what won't for some time.
Whether being a "Jack of All Trades and Master of None" or a "Master of One" is better is currently tough to judge.
If the AI Scientist continues to mature and surpass human performance levels, these old sayings may change once again! Let's wait and see, but this domain is poised for significant change!
Note: All are my personal views
Ravi Saripalle
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