An issue recently raised involves the data privacy of SIGAI and ACM members using EasyChair to submit articles for publication, including the AI Matters Newsletter. As part of entering a new submission through EasyChair, the following message appears:
“AI Matters, 2014-present, is an ACM conference. The age and gender fields are added by ACM. By providing the information requested, you will help ACM to better understand where it stands in terms of diversity to be able to focus on areas of improvement.
It is mandatory for the submitting author (but you can select “prefer not to submit”) and it is desirable that you fill it out for all authors.
This information will be deleted from EasyChair after the conference.”
To evaluate the likelihood of privacy protection, one should pay attention to the EasyChair Terms of Service, particularly Section 6 “Use of Personal Information”. More investigation may allow a better assessment of the level of risk if our members choose to enter personal information. Your Public Policy Officer is working with the other SIGAI officers to clarify the issues and make recommendations for possible changes in ACM policy.
Please send your views on this topic to SIGAI and contribute comments to this Blog.
Policy News Matters
At their annual meeting this week, the American Medical Association produced a statement “AMA Passes First Policy Recommendations on Augmented Intelligence”, adopting broad policy recommendations for health and technology stakeholders. The statement quotes AMA Board Member Jesse M. Ehrenfeld as follows: “As technology continues to advance and evolve, we have a unique opportunity to ensure that augmented intelligence is used to benefit patients, physicians, and the broad health care community. Combining AI methods and systems with an irreplaceable human clinician can advance the delivery of care in a way that outperforms what either can do alone. But we must forthrightly address challenges in the design, evaluation and implementation as this technology is increasingly integrated into physicians’ delivery of care to patients.”
In the daily news and social media, AI terms are part of the popular lexicon for better or for worse. AI technology is both praised and feared in different corners of society. Big data practitioners and even educators add confusion by misusing AI terms and concepts.
“Algorithm” and “machine learning” may be the most prevalent terms that are picked up in the popular dialogue, including in the important fields of ethics and policy. The ACM and SIGAI could have a critical educational role in the public sphere. In the area of policy, the correct use of AI terms and concepts is important for establishing credibility with the scientific community and for creating policy that addresses the real problems.
In recent weeks, interesting articles have appeared by writers diverse in the degree of scientific expertise. A June issue of The Atlantic has an article by Henry Kissinger entitled “How the Enlightenment Ends” with the thesis that society is not prepared for AI. While some of the understanding of AI concepts can be questioned, the conclusion is reasonable: “AI developers, as inexperienced in politics and philosophy as I am in technology, should ask themselves some of the questions I have raised here in order to build answers into their engineering efforts. The U.S. government should consider a presidential commission of eminent thinkers to help develop a national vision. This much is certain: If we do not start this effort soon, before long we shall discover that we started too late.”
In May, The Atlantic had an article about the other extreme of scientific knowledge by Kevin Hartnett entitled “How a Pioneer of Machine Learning Became One of Its Sharpest Critics”. He writes about an interview with Judea Pearl about his current thinking, with Dana Mackenzie, in The Book of Why: The New Science of Cause and Effect. The interview includes a criticism of deep learning research and the need for a more fundamental approach.
Back to policy, I recently attended a DC event of the Center for Data Innovation on a proposed policy framework to create accountability in the use of algorithms. They have a report on the same topic. The event was another reminder of the diverse groups in dialogue in the public sphere on critical issues for AI and the need to bring together the policymakers and the scientific community. SIGAI can have a big role to play.