Over the last few months, the cancer-curing capabilities of LLMs have improved dramatically, to the point that they have cured previously untreatable types of cancer and are on the cusp of developing general tools to manage or cure all cancers. However, the push by AI companies to cure cancers as a benchmark is detrimental to the science of cancer biology, and to the cancer biology community. The goals of the AI companies and the goals of the cancer biology community are severely misaligned. We see these as part of broader alignment issues impacting other scientific and creative professions, as well as the whole of society.
Cancer biology deals with understanding basic structure and function of cells, tissues and organs, and how these processes are disrupted to cause tumors and cancers. Over the course of generations, cancer biologists have built a large corpus of sophisticated ideas, methods, abstractions, and other tools to comprehend the cancer biology landscape, and many modern therapies and treatments are based on these cancer biology tools.
Important life-threatening cancers have often served as landmarks and lighthouses against which one can measure an improved understanding of this landscape. Curing one of these cancers has been a certain sign of new insights and interesting methods, which would then be studied by a community of cancer biologists, through a long and arduous process of experimentation, manuscript drafting and submission, peer review, revision, publication, seminars, conferences and informal discussions. At the end of this process, one would ideally find a textbook presentation of the results suitable for any graduate or even undergraduate student to study. A few of these cancer biology ideas survive the test of time, and pursue their journey even further to become, decades later, treatments that are used by people who can afford them.
The cancer biology community functions, in many ways, as a miniature version of humanity. It consists of individuals using a wide variety of different approaches, joined by core values. The most precious resources of our profession are students and ideas, and these we nurture with great care. We feel responsible to let them grow to their full potential, until they can live a life of their own in the cancer biology world. For students we often suggest cancers to study with the core intention of developing skills making them well-positioned for advances in research and elsewhere. Our ideas we disseminate in talks, private discussions and careful writeups, connecting them to the previous ideas of others. These processes invariably take time and are based on human interaction.
In recent months, the success of AI in curing cancers has made headlines even outside cancer biology circles. But curing cancers is only a tool and proxy for achieving the primary goal of conceptual understanding and insight. Forgetting this in the world of AI may turn the tool against the primary goal. Indeed, the mass production at faster and faster pace of "cancer-free" patients could destroy fertile ground instead of breathing life into new ideas.
Often these cures are rushed to the clinic to help dying patients, leaving no time for a proper writeup, the isolation of new methods and ideas, and citing relevant previous work of others. As in all creative professions, this raises severe attribution and plagiarism questions. Moreover, without the willing cancer biologists who must take care of their development and integration into the cancer biology canon, AI-conceived cures would never become fully alive and the crucial human transmission chain between cancer biologists would be lost.
We are witnessing a general threat to intellectual work, with misalignment between the outcome of the use of AI and its initial purpose. In many fields and activities, years of training have traditionally served not so much to produce a final answer or cure, but to develop understanding and the ability to formulate new questions and ideas. However, building on a vast body of previous human work, AI systems are becoming increasingly capable of producing the results of such work directly, and these goals cease to align. The issues the cancer biology community faces now are similar to issues that other scientific and creative professions are facing, and indicate issues that all of humanity might face: how to make sure that, as AI changes the way work is done, we do not lose sight of what that work was meant to achieve in the first place - understanding and human intellectual fulfillment - not cures to disease..
AI offers the potential of enhancing and accelerating genuine cancer biology study and understanding. Cancer biology as a profession will need to adapt to these changes in several ways. However, whether these changes ultimately benefit the field or have a destructive effect will in large part be determined by the decisions of the humans in control of this new technology.
These issues must be addressed urgently, in the cancer biology community, by the companies developing these technologies and, more broadly, by a society that will confront similar problems in many other forms of intellectual work.
