Artificial intelligence is poised to significantly impact various fields and activities, transforming how we approach creativity, professional activities, science, and many more domains. Disruption will accelerate the development of new innovative businesses and strategies in finance, medicine, data management, systems engineering, materials science, art, and other industries. AI’s impact will be profound and multifaceted, driving innovation and efficiency and posing challenges regarding ethics, job displacement, and new skills and regulations. As AI continues to evolve, its integration into these areas will likely shape the future of human society in significant ways.
The first gene-edited approved drug (treating sickle cell anemia) is the first commercial rewriting of human genomes. Is this a new “Golden Age” for medicine? There is great promise, and the potential to treat unmet medical needs, scale dramatic innovations to commercial applications, and transform life sciences is enormous. Since every medicine is an intersection of scientific, technical, and clinical understanding, many new treatments are suddenly arriving because of the convergence of dramatic advancements in science, technical knowledge, and clinical results. Modern medicine is witnessing a transformative era of groundbreaking innovations and technological advancements. We are witnessing a renaissance in drug treatment driven by innovations in immunotherapy, weight management, vaccine development, gene editing, and AI. These advances reshape medical treatments and fundamentally alter our approach to health and disease. As these technologies mature and their applications broaden, the future of medicine holds unprecedented potential for improving human health and longevity. A golden age – with a bit of hype.
Our most intractable problems cannot be solved with behavior modification, conservation, or our existing technology, regardless of its advanced or widespread applications.
Only new knowledge creating innovative solutions can address our most intractable problems. This can only be achieved through basic scientific discoveries and then combining these discoveries with enterprise-based innovation, commercial discipline, and competition. Innovation, creativity, and competitive dynamics create the most effective innovations, the best solutions, and the most sustainable companies. Developing the best public policy as well as the best structure to enable innovative and creative solutions, as well as the economic incentive to scale these opportunities and make them economically sustainable.
Central planning, bureaucratic industrial policy, government-led economic management, and dictatorial focus have always failed, and always will.
Most current innovations have yet to reach their potential, and new innovations are essential to address the most critical issues we confront, whether that is climate change, food scarcity, water shortages, or more effective distribution of innovation itself. Advanced technologies can be many things, but several areas, including artificial intelligence, life sciences, and software innovations provide the most potent platform for new opportunities, disruptive innovation, and value creation. Software will disrupt the most important industries in the world, especially finance, life sciences, and communications. These will be the fundamental innovations that will drive value creation over the course of the next year, and from now on.
Transformation, or euphemistically, “disruption,” creates great opportunities to capture newly created wealth. But, as industries are transforming and strategic disruption is occurring, quite a lot of absurdity and certainly enough terror are associated with some of these extraordinary opportunities to require much greater analysis and understanding. There are extraordinary risks associated with anything disruptive and transformational. The first disruptor isn’t always the one who creates the most value or is even a sustainable competitive entity. Innovation does not mean competitive sustainability. Digital platforms, ranging from the internet to digital assets and cryptocurrency are transforming industries globally. But, along with that comes a lot of hyperbole and typically that is followed by very little substance. Great companies use technological disruption, innovation, and transformation to establish themselves and thrive. But they rarely last. Every company, even the most valuable companies such as Apple, Apple, Amazon, Facebook, Netflix, etc. must dynamically transform to stay competitive and valuable. Transformations are certain. New entities will become very valuable, legacy companies will diminish, and a handful will transform and thrive. Transformation and sustainability create and capture great wealth, but are far more challenging to identify, and even more challenging to sustain.
Artificial intelligence, while generating powerful tools for analysis, is only the beginning of a more ambitious phase making AI systems more accurate, less biased, and effective prediction tools. Gathering more and more raw data does not create value. One cannot simply push a button and have valuable output generated. Data needs to be collected, processed, stored, managed, analyzed, and visualized – only then can we begin to interpret the results. Each step is challenging, and every step in this cycle requires massive amounts of work and value-added tools. It’s not just the software and hardware artifacts we produce that will be physically present everywhere and touch our lives all the time, it will be the computational concepts we use to approach and solve problems, manage our daily lives, and communicate and interact with other people. It will be a reality when it is so integral to our lives it disappears. The problems and solutions we address are limited only by our own curiosity and creativity.
Investors have been swept up in the notion of “philanthropic capitalism” and have targeted life-sciences as an avenue that can fulfill this benefit to society. While laudable in concept, this is non-scientific surrealism. “Hoped-for” is not a reliable business model, and most of the unrealistic goals would not be sustainable even if achieved. Real science and innovation are more impactful and substantial and make life sciences even more.
