In the SIGAI June blog posts, we covered the USACM-EUACM joint statement on Algorithmic Transparency and Accountability (ATA). This topic is being actively discussed online and in public presentations. An interesting development is an FAQ project by the USACM Algorithms Working Group, which aims “to take the lead addressing the technical aspects of algorithms and to have content prepared for media inquiries and policymakers.” The FAQ could also help raise the profile of USACM’s work if stakeholders look to it for answers on the technical underpinnings of algorithms. The questions build on issues raised in the USACM-EUACM joint statement on ATA. The briefing materials will also support a forthcoming USACM policy event.

The FAQ is interesting in its own right, and an AI Matters blog discussion could be helpful to USACM and the ongoing evolution of the ATA issue. Please make Comment to this posting so we can collect and share your input with USACM. You can also send your ideas and suggestions directly with Cynthia Florentino, ACM Policy Analyst, at

Below are the questions being discussed. The USACM Working Group will appreciate the input from SIGAI. I hope you enjoy thinking about these questions and the ideas around the issue of algorithmic transparency and accountability.

Current Questions in the DRAFT Working Document
Frequently Asked Questions
USACM Statement on Algorithmic Transparency and Accountability

Q: What is an algorithm?

Q: Can algorithms be explained? Why or why not? ? Why or why not? What are the challenges?

Q: What are the technical challenges associated with data inputs to an algorithm?

Q: What are machine learning models?

Q: What are neural networks?

Q: What are decision trees?

Q: How can we introduce checks and balances into the development and operation of software to make it impartial?

Q: When trying to introduce checks and balances, what is the impact of AI algorithms that are unable to export an explanation of their decision

Q:What lies ahead for algorithms?

Q: Who is the intended audience?

Q: Are these principles just for the US, or are they intended to applied world-wide?

Q: Are these principles for government or corporations to follow?

Q: Where did you get the idea for this project?

Q: What kind of decisions are being made by computers today?

Q: Can you give examples of biased decisions made by computer?

Q: Why is there resistance to explaining the decisions made by computer

Q: Who is responsible for biased decisions made with input from a machine learning algorithm?

Q: What are sources of bias in algorithmic decision making?

Q: What are some examples of the data sets used to train machine learning algorithms that contain bias?

Q: Human decision makers can be biased as well. Are decisions made by computers more or less biased?

Q: Can algorithms be biased even if they do not look at protected characteristics like race, gender, disability status, etc?

Q: What are some examples of proprietary algorithms being used to make decisions of public interest?

Q: Are there other sets of principles in this area?

Q: Are there other organizations is working in this area?

Q: Are there any academic courses in this area?


Your suggestions will be collected and sent to the USACM Algorithms Working Group, and  you can share your input directly with Cynthia Florentino, ACM Policy Analyst

China Matters

In a recent post, AI Matters welcomed ACM SIGAI China and its members as a chapter of ACM SIGAI.  Prof. Le Dong, University of Electronic Science and Technology of China, is the Chair of SIGAI China. The AI Matters policy blog will be exploring areas of common interest in AI policy and issues for discussions in future postings.

As their first event, ACM SIGAI China held the Symposium on New Challenges and Opportunities in the Post-Turing AI Era in May, 2017, as part of the ACM Turing 50th Celebration Conference in Shanghai. Keynote presentations addressed the challenges of bringing robotic and other AI technologies into practice, including a keynote by our own Prof. Sven Koenig on timely decision making by robots and other agents in their environments.

The Symposium included workshops that particularly relate to policy issues. The Career of the Young in the Emerging Field featured rising new scientists discussing the human responsibilities and challenges that accompany the many career opportunities in AI. The Gold-Rush Again to Western China: When ACM Meets B&R workshop focused on the Belt and Road Initiative for a Trans-Eurasia, across-ocean economic strategy and the related opportunities for computer science. The IoT and Cyberspace Security workshop explored opportunities and issues in areas of vehicular sensor networks, traffic management, intelligent and green transportation, and collection of data on people and things for operating the urban infrastructure.

We look forward to interactions with our colleagues in the ACM SIGAI China as we explore policy issues along with discussing cutting-edge research in artificial intelligence.

Algorithmic Accountability

The previous SIGAI public policy post covered the USACM-EUACM joint statement on Algorithmic Transparency and Accountability. Several interesting developments and opportunities are available for SIGAI members to discuss related topics. In particular, individuals and groups are calling for measures to provide independent oversight that might mitigate the dangers of biased, faulty, and malicious algorithms. Transparency is important for data systems and algorithms that guide life-critical systems such as healthcare, air traffic control, and nuclear control rooms. Ben Shneiderman’s Turing lecture is highly recommended on this point:

A robust discussion on the SIGAI Public Policy blog would be great for exploring ideas on oversight measures. Additionally, we should weigh in on some fundamental questions such as those raised by Ed Felton in his recent article “What does it mean to ask for an ‘explainable’ algorithm?” He sets up an excellent framework for the discussion, and the comments about his article raise differing points of view we should consider.

Felton says that “one of the standard critiques of using algorithms for decision-making about people, and especially for consequential decisions about access to housing, credit, education, and so on, is that the algorithms don’t provide an ‘explanation’ for their results or the results aren’t ‘interpretable.’  This is a serious issue, but discussions of it are often frustrating. The reason, I think, is that different people mean different things when they ask for an explanation of an algorithm’s results”.  Felton discusses four types of explainabilty:
1.  A claim of confidentiality (institutional/legal). Someone withholds relevant information about how a decision is made.
2.  Complexity (barrier to big picture understanding). Details about the algorithm are difficult to explain, but the impact of the results on a person can still be understood.
3.  Unreasonableness (results don’t make sense). The workings of the algorithm are clear, and are justified by statistical evidence, but the nature of how our world functions isn’t clear.
4.  Injustice (justification for designing the algorithm). Using the algorithm is unfair, unjust, or morally wrong.

In addition, SIGAI should provide input on the nature of AI systems and what it means to “explain” how decision-making AI technologies work – for example, the role of algorithms in supervised and unsupervised systems versus the choices of data and design options in creating an operational system.

Your comments are welcome. Also, please share what work you may be doing in the area of algorithmic transparency.

Algorithmic Transparency and Accountability

Algorithms in AI and data science software are having increasing impacts on individuals and society. Along with the many benefits of intelligent systems, potential harmful bias needs to be addressed. A USACM-EUACM joint statement was released on May 25, 2017, and can be found at See the ACM Technology Blog for discussion of the statement. The ACM US Public Policy Council approved the principles earlier this year.

In a message to USACM members, ACM Director of Public Policy Renee Dopplick, said, “EUACM has endorsed the Statement on Algorithmic Transparency and Accountability. Furthering its impacts, we are re-releasing it as a joint statement with a related media release. The USACM-EUACM Joint Statement demonstrates and affirms shared support for these principles to help minimize the potential for harm in algorithmic decision making and thus strengthens our ability to further expand our policy and media impacts.”

The joint statement aims to present the technical challenges and opportunities to prevent and mitigate potential harmful bias. The set of principles, consistent with the ACM Code of Ethics, is included in the statement and is intended to support the benefits of algorithmic decision-making while addressing these concerns.

The Principles for Algorithmic Transparency and Accountability from the joint statement are as follows:

  1. Awareness: Owners, designers, builders, users, and other stakeholders of analytic systems should be aware of the possible biases involved in their design, implementation, and use and the potential harm that biases can cause to individuals and society.
  2. Access and redress: Regulators should encourage the adoption of mechanisms that enable questioning and redress for individuals and groups that are adversely affected by algorithmically informed decisions.
  3. Accountability: Institutions should be held responsible for decisions made by the algorithms that they use, even if it is not feasible to explain in detail how the algorithms produce their results.
  4. Explanation: Systems and institutions that use algorithmic decision-making are encouraged to produce explanations regarding both the procedures followed by the algorithm and the specific decisions that are made. This is particularly important in public policy contexts.
  5. Data Provenance: A description of the way in which the training data was collected should be maintained by the builders of the algorithms, accompanied by an exploration of the potential biases induced by the human or algorithmic data-gathering process. Public scrutiny of the data provides maximum opportunity for corrections. However, concerns over privacy, protecting trade secrets, or revelation of analytics that might allow malicious actors to game the system can justify restricting access to qualified and authorized individuals.
  6. Auditability: Models, algorithms, data, and decisions should be recorded so that they can be audited in cases where harm is suspected.
  7. Validation and Testing: Institutions should use rigorous methods to validate their models and document those methods and results. In particular, they should routinely perform tests to assess and determine whether the model generates discriminatory harm. Institutions are encouraged to make the results of such tests public.

We welcome your comments in the AI Matters blog and the ACM Technology Blog.


As your public policy officer, I have joined the USACM.  My goals are to introduce AI matters into USACM discussions and to relay AI-related ideas and issues from USACM to SIGAI members through blog postings.
Here is some information about USACM:

The U.S. Public Policy Council of ACM (USACM) is chartered as the focal point for ACM’s interaction with U.S. government organizations, the computing community, and the U.S. public in all matters of U.S. public policy related to information technology and computing — except issues in science and math education relevant to computing and computer science, which is the responsibility of the Educational Policy Committee (EPC). The USACM Council superseded the former ACM U.S. Public Policy standing committee.

The USACM is authorized to take official policy positions.  These positions reflect the position of the USACM and not necessarily that of ACM. Policy positions of USACM are decided by a majority vote of the USACM Executive Committee.

Currently, USACM has the following seven standing committees listed below (with chairs):
USACM-Accessibility  Harry Hochheiser (Accessibility & usability)
USACM-DigiGov          Chris Bronk          (Digital governance)
USACM-IP                   Paul Hyland          (Intellectual property)
USACM-Law                Andy Grosso         (IT & Law)
USACM-Security         Alec Yasinsac        (Security)
USACM-Privacy          Brian Dean            (Privacy)
USACM-Voting           Barbara Simons    (Voting-related computing issues)

Working Groups
Internet of Things (USACM-IOT)
Algorithmic Accountability (USACM-Algorithms)
Big Data (USACM-Data)

Please find more information about USACM at
and the brochure at

Policy Issues for AI Discussion

Today’s blog post seeks to focus on, and initiate a discussion about, the current administration’s positions on AI R&D support and public policies. We would like to know SIGAI members’ views on the important areas of concern for AI-related policies.

In December 2016, the Obama administration released a report on Artificial Intelligence, Automation, and the Economy. This report followed the Administration’s previous report, Preparing for the Future of Artificial Intelligence, which recommended that the White House publish a report on the economic impacts of artificial intelligence by the end of 2016. The reports addressed readiness of the United States for a future in which artificial intelligence plays a growing role. The Obama Administration’s views are described in the Roadmap for AI Policy by Ajay Agrawal, Joshua Gans, and Avi Goldfarb in the December 21, 2016, Harvard Business Review. Some reference points from outside the US are Artificial intelligence: an overview for policy-makers from the U.K. and China’s planning for AI.

Miles Brundage and Joanna Bryson argued in August 2016 (see Smart Policies for Artificial Intelligence) that a de facto artificial intelligence policy already exists: “a patchwork of policies impacting the field of AI’s development in myriad ways. The key question related to AI policy, then, is not whether AI should be governed at all, but how it is currently being governed, and how that governance might become more informed, integrated, effective, and anticipatory.”

Some potential implications of AI for society involve the speed of change due to advances in AI technology; loss of individual control and privacy; job destruction due to automation; and the need for laws and public policy on AI technology’s role in the transformation of society. An important point is that, compared to the industrial revolution, AI’s impact is happening much faster and at a much larger scale of use than past technological advances. Organizations need to recognize the likelihood of disruption of operations that will happen whether or not change is intentional and planned.

In our current environment, we need to examine the extent of the new administration’s understanding of AI technology and the need for policies, laws, and planning. So far, not much information is available — from specifics about who will be the head of the National Highway Traffic Safety Agency (NHTSA), the main federal agency that regulates car safety, to the administration’s view of time scales. For example, the administration may take the position that AI will not cause job losses for many decades, which view could distort assumptions about labor market trends and lead to policy mistakes. These views on the future of AI could impact policies that promote programs to promote entrepreneurship and job creation. A few days ago an executive order established the American Technology Council with an initial focus on information technology. The status of the White House Office of Science and Technology Policy is not available on the OSTP Website. AI technology and applications will continue to grow rapidly, but whether or not public policy will keep pace is in doubt.

Please share your ideas via comments to this post and email messages to

Advocating for Science Beyond the March

Be a Force for Science: Advocating for Science Beyond the March
Wednesday, April 19, 2017 2:00 p.m. – 3:00 p.m. ET

Register Here  for the free AAAS webinar to learn about practical, concrete steps you can take to be a science advocate locally, nationally and internationally. The panel of communications and advocacy experts will share best practices on outreach topics, including:
• How to communicate the importance of evidence-based decision making    to policymakers.
• How to work with the media.
• How to share the value of science and its impact with the public.

AAAS will also unveil an online advocacy toolkit.

Erika Shugart
Executive Director
American Society for Cell Biology

Francis Slakey
Interim Director of Public Affairs
American Physical Society

Suzanne Ffolkes
Vice President of Communications

Moderator: Erin Heath
Associate Director, Office of Government Relations

Science & Technology Policy Forum

In this post, I report on my attendance at an excellent Annual AAAS Forum  on Science & Technology Policy held on March 27th in Washington, DC.

Very interesting presentations included ones on federal agency priorities by NIH Director Francis Collins and NSF Director France Córdova. While most everyone at the Forum was worried about the coming administration’s funding for R&D, several exciting initiatives were discussed such as NSF’s idea for “Harnessing Data for 21st Century Science and Engineering” and “Shaping the Human-Technology Frontier”, of particular interest to SIGAI (see a detailed description). Likewise, NIH is embarking on their “All of Us” research program aimed at extending precision medicine to all diseases.

Back to the concern about government support for science & technology funding, Matt Hourihan, who runs the R&D Budget and Policy Program at AAAS, gave preliminary perspectives on the next federal budget’s impact on R&D. See an interview with Matt.

He compared the responses by Congress in previous administrations; for example, bipartisan pushback on efforts to reduce NIH budgets. He also discussed the relative emphasis in administrations on applied vs. basic research funding in non-defense spending, and the possibility of reducing applied funding in the next budget. Key slides and details from his presentation are available.

Supporting articles, with great charts and major insights, are
The Trump Administration’s Science Budget: Toughest Since Apollo?
“In fact, there’s a strong argument to be made that the first Trump Administration budget is the toughest of the post-Apollo era for science and technology, even with substantial information gaps still to be filled in.”
First Trump Budget Proposes Massive Cuts to Several Science Agencies
While still waiting for details, “the picture that does emerge so far is one of an Administration seeking to substantially scale back the size of the federal science and technology enterprise nearly across the board – in some cases, through agency-level cuts not seen in decades.”

One more highlight was the luncheon talk by Cori Bargmann, President of Science for the Chan Zuckerberg Initiative, on long-term funding for advancing human potential and promoting equal opportunity.

Stay tuned as the R&D budget evolves!

SIGAI Statement on New Federal Policies

Draft Statement by ACM SIGAI

The SIGAI shares the concerns of its parent organization ACM about the implications of recent executive orders and statements by President Trump and his administration. We request that the administration’s current and future actions not negatively affect members of the scientific community and their work. We encourage SIGAI members to choose actions that suit their individual positions on potential threats to the conduct of scientific work and on actions that may impede the AI community from pursuing and communicating scientific work. We recommend joining actions within ACM and those of other scientific organizations such as AAAS  We request that SIGAI members share their efforts and experiences and welcome all input and feedback at

In this post, we suggest opportunities to act upon our concerns:

The March for Science on April 22nd is planned to demonstrate our passion for science and to call for support and safeguards for the scientific community. Recent policy changes have caused heightened worry among scientists.

The AAAS is calling on scientists to Be The Force For Science. They say, “The Trump Administration’s proposed budget would cripple the science and technology enterprise through short-sighted cuts to discovery science programs and critical mission agencies alike.”


SIGAI Science Policy Statement Discussion

With the events of the past several months, the officers are interested in making SIGAI’s own statement about the immediate and long term future of AI, technology, and science in the United States. The travel ban was just the first of issues that are likely to unfold and that may impede the AI community from pursuing and communicating scientific work. Other areas of immediate concern include appointments to the administration’s science positions, such as the White House Office of Science & Technology Policy, and now the looming budget cuts for non-defense spending. Depending on how AI is framed to the administration, we could be negatively impacted if, for example, AI R&D appear to be threatening jobs.

In this blog, we encourage a thorough discussion of a possible statement by SIGAI. Included in this post are ones by other groups and a draft statement to get our discussion started.

Please give your feedback as Comments to this blog post and by sending your thoughts to Larry Medsker at


DRAFT       Statement by ACM SIGAI       DRAFT

The SIGAI shares the concerns of their parent organization, ACM, about the implications of recent executive orders and statements by President Trump and his administration. We request that current and future actions will not negatively affect members of the scientific community and their work.
We encourage SIGAI members to choose actions that suit their individual positions on potential threats to the conduct of scientific work and on actions that may impede the AI community from pursuing and communicating scientific work. We recommend joining avenues within ACM and the action plans of other scientific organizations such as AAAS and the March for Science on April 22.
We request that SIGAI members share their efforts and experiences and welcome all input and feedback at


Statements by Other Groups

ACM Statement

“The Association for Computing Machinery, a global scientific and educational organization representing the computing community, expresses concern over US President Donald J. Trump’s Executive Order imposing suspension of visas to nationals of seven countries.

“The open exchange of ideas and the freedom of thought and expression are central to the aims and goals of ACM. ACM supports the statute of International Council for Science in that the free and responsible practice of science is fundamental to scientific advancement and human and environmental well-being. Such practice, in all its aspects, requires freedom of movement, association, expression and communication for scientists. All individuals are entitled to participate in any ACM activity.”

SIGARCH Statement

“The SIGARCH executive committee shares the concerns of its parent organization, ACM, about the implications of the USA president’s executive order restricting entry of certain foreign nationals to the USA. These restrictions will not only affect scientists and members of our community who live outside of the USA, but they also impact the ability of many within the USA, in particular students, to travel. SIGARCH does not believe in, nor does it endorse, discrimination based on race, gender, faith, nationality or culture and is fully committed to its mission in spite of these restrictions. SIGARCH will be working on policies to best address this situation. Meanwhile, we strongly encourage all our sponsored events to provide support (e.g., technologies for remote participation) to maximize inclusive participation of our broader scientific community worldwide. Proposals for financial support towards this end should be submitted to the SIGARCH treasurer and will be considered on a case by case basis. We encourage event organizers to share their efforts and experiences and welcome all input and feedback at”

AAAS Statement

Scientific progress depends on openness, transparency, and the free flow of ideas. The United States has always attracted and benefited from international scientific talent because of these principles.

“The American Association for the Advancement of Science (AAAS), the world’s largest general science society, has consistently encouraged international cooperation between scientists. We know that fostering safe and responsible conduct of research is essential for scientific advancement, national prosperity, and international security. Therefore, the detaining of students and scientists that have already been screened, processed, and approved to receive a visa to visit the United States is contrary to the spirit of science to pursue scholarly and professional interests. In order for science and the economy to prosper, students and scientists must be free to study and work with colleagues in other countries.

“The January 27, 2017 White House executive order on visas and immigration will discourage many of the best and brightest international students, scholars, and scientists from studying and working in the United States, or attending academic and scientific conferences. Implementation of this policy compromises the United States’ ability to attract international scientific talent and maintain scientific and economic leadership. It is in our national interest to take a balanced approach to immigration that protects national security interests and advances our scientific leadership.

“After the tragic events of September 11, 2001, as restrictions on immigration and foreign national travel were put in place to safeguard our national security, AAAS and other organizations worked closely with the Bush administration to advise on a balanced approach. We strongly recommend a similar discussion with officials in the Trump administration.”