Dale R. Corson, a nuclear physicist who died last week, is best remembered as the Cornell University President who peacefully led his campus through the turmoil and upheaval of the Vietnam era. But he also played an influential role in deliberations over the role of secrecy in scientific research.
Dr. Corson chaired a 1982 committee of the National Academy of Sciences that produced a landmark study entitled “Scientific Communication and National Security,” which became known as the Corson Report.
In sober and measured tones, the Corson Report pushed back against calls for increased secrecy in government-funded science:
“Current proponents of stricter controls advocate a strategy of security through secrecy. In the view of the Panel security by accomplishment may have more to offer as a general national strategy. The long-term security of the United States depends in large part on its economic, technical, scientific, and intellectual vitality, which in turn depends on the vigorous research and development effort that openness helps to nurture… Controls on scientific communication could adversely affect U.S. research institutions and could be inconsistent with both the utilitarian and philosophical values of an open society.”
President Reagan cited Dr. Corson in National Security Decision Directive 189, “National Policy on the Transfer of Scientific, Technical and Engineering Information,” which seemed to affirm that fundamental research should remain unrestricted to the maximum extent possible. In fact, however, that directive imperfectly reflected the input of the Corson Report, noted Harold C. Relyea in his book “Silencing Science: National Security Controls and Scientific Communication.”
Still, many of the issues identified by Dr. Corson and his colleagues, and the concerns they expressed, remain current today and have not reached an unequivocal resolution, as evidenced most recently by the latest U.S. government policy on dual use biological research.
Commercial artificial intelligence tools have recently emerged that are able to produce police reports. If the resulting reports are inaccurate, incomplete or biased, or if the process leaks confidential information, this could undermine the criminal justice system and harm citizens.
Too often, affected patients, clinicians, and regulators cannot see how the system works, why a decision was made, or whether meaningful human oversight occurred.
Existing tools from other domains, such as existing robust public engagement processes in drug development, when applied to AI deployment can help strengthen public trust in these systems and enhance perceptions of their legitimacy and the decisions they produce.
With thoughtful policy action, it is still possible to build systems that are fair, transparent, and accountable, and to earn the public trust that will ultimately determine AI’s future. We hope policymakers are ready to act.