The NIST Trustworthy and Responsible Artificial Intelligence Resource Center

Curated on Posted on by Stefaan Verhulst

About: “The NIST Trustworthy and Responsible Artificial Intelligence Resource Center (AIRC) is a platform to support people and organizations in government, industry, and academia—both in the U.S. and internationally—driving technical and scientific innovation in AI. It serves as a one-stop-shop for foundational content, technical documents, and AI toolkits such as repository hub for standards, measurement methods and metrics, and data sets. It also provides a common forum for all AI actors to engage and collaborate in the development and deployment of trustworthy and responsible AI technologies that benefit all people in a fair and equitable manner.

The NIST AIRC is developed to support and operationalize the NIST AI Risk Management Framework (AI RMF 1.0) and its accompanying playbook. To match the complexity of AI technology, the AIRC will grow over time to provide an engaging interactive space that enables stakeholders to share AI RMF case studies and profiles, educational materials and technical guidance related to AI risk management.

The initial release of the AIRC (airc.nist.gov) provides access to the foundational content, including the AI RMF 1.0, the playbook, and a trustworthy and responsible AI glossary. It is anticipated that in the coming months enhancements to the AIRC will include structured access to relevant technical and policy documents; access to a standards hub that connects various standards promoted around the globe; a metrics hub to assist in test, evaluation, verification, and validation of AI; as well as software tools, resources and guidance that promote trustworthy and responsible AI development and use. Visitors to the AIRC will be able to tailor the above content they see based on their requirements (organizational role, area of expertise, etc.).

Over time the Trustworthy and Responsible AI Resource Center will enable distribution of stakeholder produced content, case studies, and educational materials…(More)”.

National Experimental Wellbeing Statistics (NEWS)

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US Census: “The National Experimental Wellbeing Statistics (NEWS) project is a new experimental project to develop improved estimates of income, poverty, and other measures of economic wellbeing.  Using all available survey, administrative, and commercial data, we strive to provide the best possible estimates of our nation and economy.

In this first release, we estimate improved income and poverty statistics for 2018 by addressing several possible sources of bias documented in prior research.  We address biases from (1) unit nonresponse through improved weights, (2) missing income information in both survey and administrative data through improved imputation, and (3) misreporting by combining or replacing survey responses with administrative information.  Reducing survey error using these techniques substantially affects key measures of well-being.  With this initial set of experimental estimates, we estimate median household income is 6.3 percent higher than in survey estimates, and poverty is 1.1 percentage points lower. These changes are driven by subpopulations for which survey error is particularly relevant. For householders aged 65 and over, median household income is 27.3 percent higher, and poverty is 3.3 percentage points lower than in survey estimates. We do not find a significant impact on median household income for householders under 65 or on child poverty. 

We will continue research (1) to estimate income at smaller geographies, through increased use of American Community Survey data, (2) addressing other potential sources of bias, (3) releasing additional years of statistics, particularly more timely estimates, and (4) extending the income concepts measured.  As we advance the methods in future releases, we expect to revise these estimates…(More)”.

Advancing Technology for Democracy

Curated on Posted on by Stefaan Verhulst

The White House: “The first wave of the digital revolution promised that new technologies would support democracy and human rights. The second saw an authoritarian counterrevolution. Now, the United States and other democracies are working together to ensure that the third wave of the digital revolution leads to a technological ecosystem characterized by resilience, integrity, openness, trust and security, and that reinforces democratic principles and human rights.

Together, we are organizing and mobilizing to ensure that technologies work for, not against, democratic principles, institutions, and societies.  In so doing, we will continue to engage the private sector, including by holding technology platforms accountable when they do not take action to counter the harms they cause, and by encouraging them to live up to democratic principles and shared values…

Key deliverables announced or highlighted at the second Summit for Democracy include:

  • National Strategy to Advance Privacy-Preserving Data Sharing and Analytics. OSTP released a National Strategy to Advance Privacy-Preserving Data Sharing and Analytics, a roadmap for harnessing privacy-enhancing technologies, coupled with strong governance, to enable data sharing and analytics in a way that benefits individuals and society, while mitigating privacy risks and harms and upholding democratic principles.  
  • National Objectives for Digital Assets Research and Development. OSTP also released a set of National Objectives for Digital Assets Research and Development, whichoutline its priorities for the responsible research and development (R&D) of digital assets. These objectives will help developers of digital assets better reinforce democratic principles and protect consumers by default.
  • Launch of Trustworthy and Responsible AI Resource Center for Risk Management. NIST announced a new Resource Center, which is designed as a one-stop-shop website for foundational content, technical documents, and toolkits to enable responsible use of AI. Government, industry, and academic stakeholders can access resources such as a repository for AI standards, measurement methods and metrics, and data sets. The website is designed to facilitate the implementation and international alignment with the AI Risk Management Framework. The Framework articulates the key building blocks of trustworthy AI and offers guidance for addressing them.
  • International Grand Challenges on Democracy-Affirming Technologies. Announced at the first Summit, the United States and the United Kingdom carried out their joint Privacy Enhancing Technology Prize Challenges. IE University, in partnership with the U.S. Department of State, hosted the Tech4Democracy Global Entrepreneurship Challenge. The winners, selected from around the world, were featured at the second Summit….(More)”.

Could a Global “Wicked Problems Agency” Incentivize Data Sharing?

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Paper by Susan Ariel Aaronson: “Global data sharing could help solve “wicked” problems (problems such as climate change, terrorism and global poverty that no one knows how to solve without creating further problems). There is no one or best way to address wicked problems because they have many different causes and manifest in different contexts. By mixing vast troves of data, policy makers and researchers may find new insights and strategies to address these complex problems. National and international government agencies and large corporations generally control the use of such data, and the world has made little progress in encouraging cross-sectoral and international data sharing. This paper proposes a new international cloud-based organization, the “Wicked Problems Agency,” to catalyze both data sharing and data analysis in the interest of mitigating wicked problems. This organization would work to prod societal entities — firms, individuals, civil society groups and governments — to share and analyze various types of data. The Wicked Problems Agency could provide a practical example of how data sharing can yield both economic and public good benefits…(More)”.

Automating Public Services: Learning from Cancelled Systems

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Report by Joanna Redden, Jessica Brand, Ina Sander and Harry Warne: “Pressure on public finances means that governments are trying to do more with less. Increasingly, policymakers are turning to technology to cut costs. But what if this technology doesn’t work as it should?

This report looks at the rise and fall of automated decision systems (ADS). If you’ve tried to get medical advice over the phone recently you’ve got some experience of an ADS – a computer system or algorithm designed to help or replace human decision making. These sorts of systems are being used by governments to consider when and how to act. The stakes are high. For example, they’re being used to try to detect crime and spot fraud, and to determine whether child protective services should act.

This study identifies 61 occasions across Australia, Canada, Europe, New Zealand and the United States when ADS projects were cancelled or paused. From this evidence, we’ve made recommendations designed to increase transparency and to protect communities and individuals…(More)”.

Mini Data Centers heat local swimming pools for free

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Springwise: “It is now well-understood that data centres consume vast amounts of energy. This is because the banks of servers in the data centres require a lot of cooling, which, in turn, uses a lot of energy. But one data centre has found a use for all the heat that it generates, a use that could also help public facilities such as swimming pools save money on their energy costs.

Deep Green, which runs data centres, has developed small edge data centres that can be installed locally and divert some of their excess heat to warm leisure centres and public swimming pools. The system, dubbed a “digital boiler”, involves immersing central processing unit (CPU) servers in special cooling tubs, which use oil to remove heat from the servers. This oil is then passed through a heat exchanger, which removes the heat and uses it to warm buildings or swimming pools.

Photo source Deep Green

The company says the heat donation from one of its digital boilers will cut a public swimming pool’s gas requirements by around 70 per cent, saving leisure centres thousands of pounds every year while also drastically reducing carbon emissions. Deep Green pays for the electricity it uses and donates the heat for free. This is a huge benefit, as Britain’s public swimming pools are facing massive increases in heating bills, which is causing many to close or restrict their hours…(More)”.

Policy Guide on Social Impact Measurement for the Social and Solidarity Economy

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OECD Report: “As social and solidarity economy (SSE) entities are increasingly requested to demonstrate their positive contribution to society, social impact measurement can help them understand the additional, net value generated by their activities, in the pursuit of their mission and beyond. Policy plays an important role to facilitate a conducive environment to unlock the uptake of social impact measurement among SSE actors. Drawing on a mapping exercise and good practice examples from over 33 countries, this international policy guide navigates how policy makers can support social impact measurement for the social and solidarity economy by: (i) improving the policy framework, (ii) delivering guidance, (iii) building evidence and (iv) supporting capacity. Building on the earlier publication Social Impact Measurement for the Social and Solidarity Economy released in 2021 the guide is published under the framework of the OECD Global Action “Promoting Social and Solidarity Economy Ecosystems”, funded by the European Union’s Foreign Partnership Instrument…(More)”.

Building Trust in AI: A Landscape Analysis of Government AI Programs

Curated on Posted on by Stefaan Verhulst

Paper by Susan Ariel Aaronson: “As countries around the world expand their use of artificial intelligence (AI), the Organisation for Economic Co-operation and Development (OECD) has developed the most comprehensive website on AI policy, the OECD.AI Policy Observatory. Although the website covers public policies on AI, the author of this paper found that many governments failed to evaluate or report on their AI initiatives. This lack of reporting is a missed opportunity for policy makers to learn from their programs (the author found that less than one percent of the programs listed on the OECD.AI website had been evaluated). In addition, the author found discrepancies between what governments said they were doing on the OECD.AI website and what they reported on their own websites. In some cases, there was no evidence of government actions; in other cases, links to government sites did not work. Evaluations of AI policies are important because they help governments demonstrate how they are building trust in both AI and AI governance and that policy makers are accountable to their fellow citizens…(More)”.

Data Collaborative Case Study: NYC Recovery Data Partnership

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Report by the Open Data Policy Lab (The GovLab): “In July 2020, following severe economic and social losses due to the COVID-19 pandemic, the administration of New York City Mayor Bill de Blasio announced the NYC Recovery Data Partnership. This data collaborative asked private and civic organizations with assets relevant to New York City to provide their data to the city. Senior city leaders from the First Deputy Mayor’s Office, the Mayor’s Office of Operations, Mayor’s Office of Information Privacy and Mayor’s Office of Data Analytics formed an internal coalition which served as trusted intermediaries, assessing agency requests from city agencies to use the data provided and allocating access accordingly. The data informed internal research conducted by various city agencies, including New York City Emergency Management’s Recovery Team and the NYC…(More)”Department of City Planning. The experience reveals the ability of crises to spur innovation, the value of responsiveness from both data users and data suppliers, and the importance of technical capacity, and the value of a network of peers. In terms of challenges, the experience also exposes the limitations of data, the challenges of compiling complex datasets, and the role of resource constraints.

Mapping Diversity

Curated on Posted on by Stefaan Verhulst

About: “Mapping Diversity is a platform for discovering key facts about diversity and representation in street names across Europe, and to spark a debate about who is missing from our urban spaces.

We looked at the names of 145,933 streets across 30 major European cities, located in 17 different countries. More than 90% of the streets named after individuals are dedicated to white men. Where did all the other inhabitants of Europe end up? The lack of diversity in toponymy speaks volumes about our past and contributes to shaping Europe’s present and future…(More)”.