Artificial intelligence

NSF will fund $120 million to advance artificial intelligence innovation

National Artificial Intelligence Research Institutes
Photo: National Science Foundation

The National Science Foundation announced $120 million in funding for a new organization — the National Artificial Intelligence Research Institutes — “that will significantly advance research in AI and accelerate the development of transformational, AI-powered innovation.”

From the announcement:

The program, led by NSF in partnership with the National Institute of Food and Agriculture, U.S. Department of Homeland Security’s Science & Technology Directorate, U.S. Department of Transportation’s Federal Highway Administration and U.S. Department of Veterans Affairs, has both planning and institute tracks. The planning track will support planning grants for up to two years and $500,000 to enable teams to develop collaborative plans and capacity for full institute operations. The institute track will support cooperative agreements of $16 million to $20 million for four to five years (up to $4 million per year) for the creation of AI Research Institutes in an initial set of high-priority areas:

Trustworthy AI

Foundations of Machine Learning

AI-Driven Innovation in Agriculture and the Food System

AI-Augmented Learning

AI for Accelerating Molecular Synthesis and Manufacturing

AI for Discovery in Physics

Earlier this year, NSF joined other federal agency partners in announcing the release of the 2019 Update to the National Artificial Intelligence (AI) Research and Development (R&D) Strategic Plan. In addition, Advances in AI are core to many of the “10 Big Ideas for Future NSF Investments,” key among these being Harnessing the Data Revolution and the Future of Work at the Human-Technology Frontier.

More: NSF leads federal partners in accelerating the development of transformational, AI-powered innovation

UK will pilot AI government procurement guidelines co-designed with World Economic Forum

Photo: World Economic Forum
Photo: World Economic Forum

The United Kingdom Government announced it will pilot newly-developed artificial intelligence procurement guidelines it co-designed with the World Economic Forum.

From the announcement:

Governments want to acquire AI solutions to streamline processes and provide insights into key sectors such as transportation, healthcare and public services. However, officials often lack experience in acquiring such solutions and many public institutions are cautious about harnessing this rapidly developing technology at a time when we are only beginning to understand the risks as well as the opportunities.

Growing public concerns around bias, privacy, accountability and transparency of the technology has added an extra layer of complexity to a potential roll out on a national level. The AI Procurement Guidelines for Governments have been designed help officials keep up with this rapidly developing technology and mitigate the risks.

The guidelines were co-designed by the World Economic Forum’s Artificial Intelligence and Machine Learning team and fellows embedded from UK Government’s Office of AI, Deloitte, Salesforce and Splunk. Members of government, academia, civil society and the private sector were consulted throughout a ten-month development process, which incorporated workshops and interviews with government procurement officials and private sector procurement professionals.

The report provides the requirements a government official should address before acquiring and deploying AI solutions and services. It also provides the questions that companies should answer about their AI development and how the data is used and processed. The guidelines also include explanatory text elaborating on how to implement, key questions to ask and case studies.

More: UK Government First to Pilot AI Procurement Guidelines Co-Designed with World Economic Forum

In-Q-Tel explains explainable artificial intelligence

Explainable articifical intelligence
Photo: In-Q-Tel

The intelligence community’s venture capital arm, In-Q-Tel, published a helpful primer on explainable artificial intelligence.

I’m not an expert in AI and, if you’re not either, these excerpts may elevate your understanding:

As use of AI and Machine Learning (ML) becomes increasingly common across industries and functions, interdisciplinary stakeholders are searching for ways to understand the systems they are using so that they can trust the decisions such systems inform. This effort is sometimes referred to as “Explainable AI” or “XAI”.

The focus on trust and understanding that is driving the XAI movement relates to important questions of law and policy. An explanation for an AI or ML system can put the system’s reasoning into the open for debate about whether it is equitable or just, or may enable some sort of actionable understanding around why a decision was made.(5)

Some researchers, like Facebook’s Chief AI Scientist Yann Lecun and Google Brain’s Geoff Hinton, have argued that asking systems to “explain” themselves is a complex, infeasible task that may not lead to actionable insight.(6,7) Others disagree, arguing that explainability is necessary, as technologists need to consider the social implications of all parts of their AI systems.(8,9,10) Moreover, they argue, evolving research may make the task increasingly feasible.(11)

One helpful way to characterize efforts in XAI is by applicability — for example, whether a technique can be used to interpret or justify a single model or many, or whether it can be used to interpret or justify a single decision or larger trends.

While most new work and research on these techniques is coming from the academic sector, XAI tools are beginning to materialize in the market. Whether XAI companies will be able to stand on their own, or if these tools will primarily be absorbed as a feature by established AI/ML players, remains to be seen.

Read more: Explainable AI