Book edited by Antony Taubman and Jayashree Watal: “Technological change has transformed the ways knowledge is developed and shared internationally. Accordingly, in the quarter-century since the WTO was established, and since its Agreement on Trade-Related Aspects of Intellectual Property Rights came into force, both the knowledge dimension of trade and the functioning of the IP system have been radically transformed. The need to understand and respond to this change has placed knowledge at the centre of policy debates about economic and social development. Recognizing the need for modern analytical tools to support policymakers and analysts, this publication draws together contributions from a diverse range of scholars and analysts. Together, they offer a fresh understanding of what it means to trade in knowledge in today’s technological and commercial environment. The publication offers insights into the prospects for knowledge-based development and ideas for updated systems of governance that promote the creation and sharing of the benefits of knowledge….(More)”.
The Global Politics of Artificial Intelligence
Book edited by Maurizio Tinnirello: “Technologies such as artificial intelligence have led to significant advances in science and medicine, but have also facilitated new forms of repression, policing and surveillance. AI policy has become without doubt a significant issue of global politics.
The Global Politics of Artificial Intelligence tackles some of the issues linked to AI development and use, contributing to a better understanding of the global politics of AI. This is an area where enormous work still needs to be done, and the contributors to this volume provide significant input into this field of study, to policymakers, academics, and society at large. Each of the chapters in this volume works as freestanding contribution, and provides an accessible account of a particular issue linked to AI from a political perspective. Contributors to the volume come from many different areas of expertise, and of the world, and range from emergent to established authors…(More)”.
When Launching a Collaboration, Keep It Agile
Essay by the Stakeholder Alignment Collaborative: “Conventional wisdom holds that large-scale societal challenges require large-scale responses. By contrast, we argue that progress on major societal challenges can and often should begin with small, agile initiatives—minimum viable consortia (MVC)—that learn and adapt as they build the scaffolding for large-scale change. MVCs can address societal challenges by overcoming institutional inertia, opposition, capability gaps, and other barriers because they require less energy for activation, reveal dead ends early on, and can more easily adjust and adapt over time.
Large-scale societal challenges abound, and organizations and institutions are increasingly looking for ways to deal with them. For example, the National Academy of Engineering (NAE) has identified 14 Grand Societal Challenges for “sustaining civilization’s continuing advancement while still improving the quality of life” in the 21st century. They include making solar energy economical, developing carbon sequestration methods, advancing health informatics, and securing cyberspace. The United Nations has set 17 Sustainable Development Goals (SDGs) to achieve by 2030 for a better future for humanity. They include everything from eliminating hunger to reducing inequality.
Tackling such universal goals requires large-scale cooperation, because existing organizations and institutions simply do not have the ability to resolve these challenges independently. Further note that the NAE’s announcement of the challenges stated that “governmental and institutional, political and economic, and personal and social barriers will repeatedly arise to impede the pursuit of solutions to problems.” The United Nations included two enabling SDGs: “peace, justice, and strong institutions” and “partnership for the goals.” The question is how to bring such large-scale partnerships and institutional change into existence.
We are members of the Stakeholder Alignment Collaborative, a research consortium of scholars at different career stages, spanning multiple fields and disciplines. We study collaboration collaboratively and maintain a very flat structure. We have published on multistakeholder consortia associated with science1 and provided leadership and facilitation for the launch and sustainment of many of these consortia. Based on our research into the problem of developing large-scale, multistakeholder partnerships, we believe that MVCs provide an answer.
MVCs are less vulnerable to the many barriers to large-scale solutions, better able to forge partnerships and a more agile framework for making needed adjustments. To demonstrate these points, we focus on examples of MVCs in the domain of scientific research data and computing infrastructure. Research data are essential for virtually all societal challenges, and an upsurge of multistakeholder consortia has occurred in this domain. But the MVC concept is not limited to these challenges, nor to digitally oriented settings. We have chosen this sphere because it offers a diversity of MVC examples for illustration….(More)”. (See also “The Potential and Practice of Data Collaboratives for Migration“).
Theory of Change Workbook: A Step-by-Step Process for Developing or Strengthening Theories of Change
USAID Learning Lab: “While over time theories of change have become synonymous with simple if/then statements, a strong theory of change should actually be a much more detailed, context-specific articulation of how we *theorize* change will happen under a program. Theories of change should articulate:
- Outcomes: What is the change we are trying to achieve?
- Entry points: Where is there momentum to create that change?
- Interventions: How will we achieve the change?
- Assumptions: Why do we think this will work?
This workbook helps stakeholders work through the process of developing strong theories of change that answers the above questions.
A strong theory of change process leads to stronger theory of change products, which include:
- the theory of change narrative: a 1-3 page description of the context, entry points within the context to enable change to happen, ultimate outcomes that will result from interventions, and assumptions that must hold for the theory of change to work and
- a logic model: a visual representation of the theory of change narrative…(More)”
The 2022 AI Index: Industrialization of AI and Mounting Ethical Concerns
Blog by Daniel Zhang, Jack Clark, and Ray Perrault: “The field of artificial intelligence (AI) is at a critical crossroad, according to the 2022 AI Index, an annual study of AI impact and progress at the Stanford Institute for Human-Centered Artificial Intelligence (HAI) led by an independent and interdisciplinary group of experts from across academia and industry: 2021 saw the globalization and industrialization of AI intensify, while the ethical and regulatory issues of these technologies multiplied….
The new report shows several key advances in AI in 2021:
- Private investment in AI has more than doubled since 2020, in part due to larger funding rounds. In 2020, there were four funding rounds worth $500 million or more; in 2021, there were 15.
- AI has become more affordable and higher performing. The cost to train an image classification has decreased by 63.6% and training times have improved by 94.4% since 2018. The median price of robotic arms has also decreased fourfold in the past six years.
- The United States and China have dominated cross-country research collaborations on AI as the total number of AI publications continues to grow. The two countries had the greatest number of cross-country collaborations in AI papers in the last decade, producing 2.7 times more joint papers in 2021 than between the United Kingdom and China—the second highest on the list.
- The number of AI patents filed has soared—more than 30 times higher than in 2015, showing a compound annual growth rate of 76.9%.
At the same time, the report also highlights growing research and concerns on ethical issues as well as regulatory interests associated with AI in 2021:
- Large language and multimodal language-vision models are excelling on technical benchmarks, but just as their performance increases, so do their ethical issues, like the generation of toxic text.
- Research on fairness and transparency in AI has exploded since 2014, with a fivefold increase in publications on related topics over the past four years.
- Industry has increased its involvement in AI ethics, with 71% more publications affiliated with industry at top conferences from 2018 to 2021.
- The United States has seen a sharp increase in the number of proposed bills related to AI; lawmakers proposed 130 laws in 2021, compared with just 1 in 2015. However, the number of bills passed remains low, with only 2% ultimately becoming law in the past six years.
- Globally, AI regulation continues to expand. Since 2015, 18 times more bills related to AI were passed into law in legislatures of 25 countries around the world and mentions of AI in legislative proceedings also grew 7.7 times in the past six years….(More)”
The need to represent: How AI can help counter gender disparity in the news
Blog by Sabrina Argoub: “For the first in our new series of JournalismAI Community Workshops, we decided to look at three recent projects that demonstrate how AI can help raise awareness on issues with misrepresentation of women in the news.
The Political Misogynistic Discourse Monitor is a web application and API that journalists from AzMina, La Nación, CLIP, and DataCrítica developed to uncover hate speech against women on Twitter.
When Women Make Headlines is an analysis by The Pudding of the (mis)representation of women in news headlines, and how it has changed over time.
In the AIJO project, journalists from eight different organisations worked together to identify and mitigate biases in gender representation in news.
We invited, Bàrbara Libório of AzMina, Sahiti Sarva of The Pudding, and Delfina Arambillet of La Nación, to walk us through their projects and share insights on what they learned and how they taught the machine to recognise what constitutes bias and hate speech….(More)”.
GovTech Case Studies: Solutions that Work
Worldbank: “A series of GovTech case study notes — GovTech Case Studies: Solutions that Work — provides a better understanding of GovTech focus areas by introducing concrete experiences of adopting GovTech solutions, lessons learned and what worked or did not work.
Take a sneak peek at the first set of case studies which explores GovTech solutions implemented in Brazil, Cambodia, Georgia, Lesotho, Myanmar, and Nigeria….
Crowdsourcing and COVID-19: How public administrations mobilize crowds to find solutions to problems posed by the pandemic
Paper by Ana Colovic, Annalisa Caloffi, and Federica Rossi: “We discuss how public administrations have used crowdsourcing to find solutions to specific problems posed by the COVID-19 pandemic, and to what extent crowdsourcing has been instrumental in promoting open innovation and service co-creation. We propose a conceptual typology of crowdsourcing challenges based on the degree of their openness and collaboration with the crowd that they establish. Using empirical evidence collected in 2020 and 2021, we examine the extent to which these types have been used in practice. We discuss each type of crowdsourcing challenge identified and draw implications for public policy…(More)”.
“Medical Matchmaking” provides personalized insights
Matthew Hempstead at Springwise: “Humanity is a collection of unique individuals who represent a complex mixture of medical realities. Yet traditional medicine is based on a ‘law of averages’ – treating patients based on generalisations about the population as a whole. This law of averages can be misleading, and in a world where the average American spends 52 hours looking for health information online each year, generalisations create misunderstandings. Information provided by ‘Dr. Google’ or Facebook is inadequate and doesn’t account for the specific characteristics of each individual.
Israeli startup Alike has come up with a novel multidisciplinary solution to this problem – using health data and machine learning to match people who are alike on a holistic level. The AI’s matchmaking takes into account considerations such as co-morbidities, lifestyle factors, age, and gender.
Patients are then put into contact with an anonymised community of ‘Alikes’ – people who share their exact clinical journey, lifestyle, and interests. Members of this community can share or receive relevant and personalised insights that help them to better manage their conditions.
The new technology is possible due to regulatory changes that make it possible for everyone to gain instant electronic access to their personal health records. The app allows users to automatically create a health profile through a direct connection with their health provider.
Given the sensitive nature of medical information, Alike has put in place stringent privacy controls. The data shared on the app is completely de-identified, which means all personal identifiers are removed. Every user is verified by their healthcare provider, and further measures including data encryption and data fuzzing are employed. This means that patients can benefit from the insights of other patients while maintaining their privacy…(More)”.
The New Rules of Data Privacy
Essay by Hossein Rahnama and Alex “Sandy” Pentland: “The data harvested from our personal devices, along with our trail of electronic transactions and data from other sources, now provides the foundation for some of the world’s largest companies. Personal data also the wellspring for millions of small businesses and countless startups, which turn it into customer insights, market predictions, and personalized digital services. For the past two decades, the commercial use of personal data has grown in wild-west fashion. But now, because of consumer mistrust, government action, and competition for customers, those days are quickly coming to an end.
For most of its existence, the data economy was structured around a “digital curtain” designed to obscure the industry’s practices from lawmakers and the public. Data was considered company property and a proprietary secret, even though the data originated from customers’ private behavior. That curtain has since been lifted and a convergence of consumer, government, and market forces are now giving users more control over the data they generate. Instead of serving as a resource that can be freely harvested, countries in every region of the world have begun to treat personal data as an asset owned by individuals and held in trust by firms.
This will be a far better organizing principle for the data economy. Giving individuals more control has the potential to curtail the sector’s worst excesses while generating a new wave of customer-driven innovation, as customers begin to express what sort of personalization and opportunity they want their data to enable. And while Adtech firms in particular will be hardest hit, any firm with substantial troves of customer data will have to make sweeping changes to its practices, particularly large firms such as financial institutions, healthcare firms, utilities, and major manufacturers and retailers.
Leading firms are already adapting to the new reality as it unfolds. The key to this transition — based upon our research on data and trust, and our experience working on this issue with a wide variety of firms — is for companies to reorganize their data operations around the new fundamental rules of consent, insight, and flow…(More)”.