Speaking in Tongues — Teaching Local Languages to Machines

Curated on Posted on by Stefaan Verhulst

Report by DIAL: “…Machines learn to talk to people by digesting digital content in languages people speak through a technique called Natural Language Processing (NLP). As things stand, only about 85 of the world’s approximately 7500 languages are represented in the major NLPs — and just 7 languages, with English being the most advanced, comprise the majority of the world’s digital knowledge corpus. Fortunately, many initiatives are underway to fill this knowledge gap. My new mini-report with Digital Impact Alliance (DIAL) highlights a few of them from Serbia, India, Estonia, and Africa.

The examples in the report are just a subset of initiatives on the ground to make digital services accessible to people in their local languages. They are a cause for excitement and hope (tempered by realistic expectations). A few themes across the initiatives include –

  • Despite the excitement and enthusiasm, most of the programs above are still at a very nascent stage — many may fail, and others will require investment and time to succeed. While countries such as India have initiated formal national NLP programs (one that is too early to assess), others such as Serbia have so far taken a more ad hoc approach.
  • Smaller countries like Estonia recognize the need for state intervention as the local population isn’t large enough to attract private sector investment. Countries will need to balance their local, cultural, and political interests against commercial realities as languages become digital or are digitally excluded.
  • Community engagement is an important component of almost all initiatives. India has set up a formal crowdsourcing program; other programs in Africa are experimenting with elements of participatory design and crowd curation.
  • While critics have accused ChatGPT and others of paying contributors from the global south very poorly for their labeling and other content services; it appears that many initiatives in the south are beginning to dabble with payment models to incentivize crowdsourcing and sustain contributions from the ground.
  • The engagement of local populations can ensure that NLP models learn appropriate cultural nuances, and better embody local social and ethical norms…(More)”.

Harnessing Data Innovation for Migration Policy: A Handbook for Practitioners

Curated on Posted on by Stefaan Verhulst

Report by IOM: “The Practitioners’ Handbook provides first-hand insights into why and how non-traditional data sources can contribute to better understanding migration-related phenomena. The Handbook aims to (a) bridge the practical and technical aspects of using data innovations in migration statistics, (a) demonstrate the added value of using new data sources and innovative methodologies to analyse key migration topics that may be hard to fully grasp using traditional data sources, and (c) identify good practices in addressing issues of data access and collaboration with multiple stakeholders (including the private sector), ethical standards, and security and data protection issues…(More)” See also Big Data for Migration Alliance.

The Future of Consent: The Coming Revolution in Privacy and Consumer Trust

Curated on Posted on by Stefaan Verhulst

Report by Ogilvy: “The future of consent will be determined by how we – as individuals, nations, and a global species – evolve our understanding of what counts as meaningful consent. For consumers and users, the greatest challenge lies in connecting consent to a mechanism of relevant, personal control over their data. For businesses and other organizations, the task will be to recast consent as a driver of positive economic outcomes, rather than an obstacle.

In the coming years of digital privacy innovation, regulation, and increasing market maturity, everyone will need to think more deeply about their relationship with consent. As an initial step, we’ve assembled this snapshot on the current and future state of (meaningful) consent: what it means, what the obstacles are, and which critical changes we need to embrace to evolve…(More)”.

A Guide to Adaptive Government: Preparing for Disruption

Curated on Posted on by Stefaan Verhulst

Report by Nicholas D. Evans: “With disruption now the norm rather than the exception, governments need to rethink business as usual and prepare for business as disrupted.

Government executives and managers should plan for continuous disruption and for how their agencies and departments will operate under continuous turbulence and change. In 2022 alone, the world witnessed war in Ukraine, the continuing effects of the COVID-19 pandemic, and natural disasters such as Hurricane Ian—not to mention energy scarcity, supply chain shortages, the start of a global recession, record highs for inflation, and rising interest rates.

Traditional business continuity and disaster recovery playbooks and many other such earlier approaches—born when disruption was the exception—are no longer sufficient. Rather than operating “business as usual,” government agencies and departments now must plan and operate for “business as disrupted.” One other major pivot point: when these disruptions happen, such as COVID, they bring an opportunity to drive a long awaited or postponed transformation. It is about leveraging that opportunity for change and not simply returning to the status quo The impact to supply chains during the COVID-19 pandemic and recovery illustrates this insight…

Evans recognizes the importance of pursuing agile principles as foundational in realizing the vision of adaptive government described in this report. Agile government principles serve as a powerful foundation for building “intrinsic agility,” since they encourage key cultural, behavioral, and growth mindset approaches to embed agility and adaptability into organizational norms and processes. Many of the insights, guidance, and recommendations offered in this report complement work pursued by the Agile Government Center (AGC), led by the National Academy of Public Administration in collaboration with our Center, and spearheaded by NAPA Fellow and Center Executive Fellow Ed DeSeve.

This report illustrates the strategic significance of adaptability to government organizations today. The author offers new strategies, techniques, and tools to accelerate digital transformation, and better position government agencies to respond to the next wave of both opportunities and disruptive threats—similar to what our Center, NAPA, and partner organizations refer to as “future shocks.” Adaptability as a core competency can support both innovation and risk management, helping governments to optimize for ever-changing mission needs and ambient conditions Adaptability represents a powerful enabler for modern government and enterprise organizations.

We hope that this report helps government leaders, academic experts, and other stakeholders to infuse adaptive thinking throughout the public sector, leading to more effective operations, better outcomes, and improved performance in a world where the only constant seems to be the inevitability of change and disruption…(More)”.

Workforce ecosystems and AI

Curated on Posted on by Stefaan Verhulst

Report by David Kiron, Elizabeth J. Altman, and Christoph Riedl: “Companies increasingly rely on an extended workforce (e.g., contractors, gig workers, professional service firms, complementor organizations, and technologies such as algorithmic management and artificial intelligence) to achieve strategic goals and objectives. When we ask leaders to describe how they define their workforce today, they mention a diverse array of participants, beyond just full- and part-time employees, all contributing in various ways. Many of these leaders observe that their extended workforce now comprises 30-50% of their entire workforce. For example, Novartis has approximately 100,000 employees and counts more than 50,000 other workers as external contributors. Businesses are also increasingly using crowdsourcing platforms to engage external participants in the development of products and services. Managers are thinking about their workforce in terms of who contributes to outcomes, not just by workers’ employment arrangements.

Our ongoing research on workforce ecosystems demonstrates that managing work across organizational boundaries with groups of interdependent actors in a variety of employment relationships creates new opportunities and risks for both workers and businesses. These are not subtle shifts. We define a workforce ecosystem as:

A structure that encompasses actors, from within the organization and beyond, working to create value for an organization. Within the ecosystem, actors work toward individual and collective goals with interdependencies and complementarities among the participants.

The emergence of workforce ecosystems has implications for management theory, organizational behavior, social welfare, and policymakers. In particular, issues surrounding work and worker flexibility, equity, and data governance and transparency pose substantial opportunities for policymaking.

At the same time, artificial intelligence (AI)—which we define broadly to include machine learning and algorithmic management—is playing an increasingly large role within the corporate context. The widespread use of AI is already displacing workers through automation, augmenting human performance at work, and creating new job categories…(More)”.

Including the underrepresented

Curated on Posted on by Stefaan Verhulst

Paper by FIDE: “Deliberative democracy is based on the premise that all voices matter and that we can equally participate in decision-making. However, structural inequalities might prevent certain groups from being recruited for deliberation, skewing the process towards the socially privileged. Those structural inequalities are also present in the deliberation room, which can lead to unconscious (or conscious) biases that hinder certain voices while amplifying others. This causes particular perspectives to influence decision-making unequally.

This paper presents different methods and strategies applied in previous processes to increase the inclusion of underrepresented groups. We distinguish strategies for the two critical phases of the deliberative process: recruitment and deliberation…(More)”.

Data Maturity Assessment for Government

Curated on Posted on by Stefaan Verhulst

UK Government: “The Data Maturity Assessment (DMA) for Government is a robust and comprehensive framework, designed by the public sector for the public sector. The DMA represents a big step forward in our shared ambition to establish and strengthen the data foundations in government by enabling a granular view of the current status of our data environments.

The systematic and detailed picture that the DMA results provide can be used to deliver value in the data function and across the enterprise. Maturity results, and the progression behaviours/features outlined in the DMA, will be essential to reviewing and setting data strategy. DMA outputs provide a way to communicate and evidence how the data ecosystem is critical to the business. When considered in the context of organisational priorities and responsibilities, DMA outputs can assist in:

  • identifying and mitigating strategic risk arising from low data maturity, and where higher maturity needs to be maintained
  • targeting and prioritising investment in the most important data initiatives
  • assuring the data environment for new services and programmes…(More)”.

Soft power, hard choices: Science diplomacy and the race for solutions

Curated on Posted on by Stefaan Verhulst

Article by Stephan Kuster and Marga Gual Soler: “…Global challenges demand that we build consensus for action. But reaching agreement on how – and even if – science and technology should be applied, for the aggregate benefit of all, is complex, and increasingly so.

Science and technology are tightly intertwined with fast-changing economic, geopolitical, and ideological agendas. That pace of change complicates, and sometimes deviates, the discussions and decisions that could unlock the positive global impact of scientific advances.

Therefore, anticipation is key. Understanding the societal, economic, and geopolitical consequences of emerging and possible new technologies before they are deployed is critical. Just recently, for example, artificial intelligence (AI) labs have been urged by a large number of researchers and leading industry figures to pause the training of powerful AI systems, given the inherent risks to society and humanity’s existence.

Indeed, the rapid pace of scientific development calls for more effective global governance when it comes to emerging technology. That in turn requires better anticipatory tools and new mechanisms to embed the science community as key stakeholder and influencer in this work.

The Geneva Science and Diplomacy Anticipator (GESDA) was created with those goals in mind. GESDA identifies the most significant science breakthroughs in the next five, 10, and 25 years. It assesses those advances with the potential to most profoundly to impact people, society, and the planet. It then brings together scientific and policy leaders from around the world to devise the diplomatic envelopes and approaches needed to embrace these advances, while minimizing downsides risks of unintended consequences…(More)”.

The Technology/Jobs Puzzle: A European Perspective

Curated on Posted on by Stefaan Verhulst

Blog by Pierre-Alexandre Balland, Lucía Bosoer and Andrea Renda as part of the work of the Markle Technology Policy and Research Consortium: “In recent years, the creation of “good jobs” – defined as occupations that provide a middle-class living standard, adequate benefits, sufficient economic security, personal autonomy, and career prospects (Rodrik and Sabel 2019; Rodrik and Stantcheva 2021) – has become imperative for many governments. At the same time, developments in industrial value chains and in digital technologies such as Artificial Intelligence (AI) create important challenges for the creation of good jobs. On the one hand, future good jobs may not be found only in manufacturing, ad this requires that industrial policy increasingly looks at services. On the other hand, AI has shown the potential to automate both routine and also non-routine tasks (TTC 2022), and this poses new, important questions on what role humans will play in the industrial value chains of the future. In the report drafted for the Markle Technology Policy and Research Consortium on The Technology/Jobs Puzzle: A European Perspective, we analyze Europe’s approach to the creation of “good jobs”. By mapping Europe’s technological specialization, we estimate in which sectors good jobs are most likely to emerge, and assess the main opportunities and challenges Europe faces on the road to a resilient, sustainable and competitive future economy.The report features an important reflection on how to define job quality and, relatedly “good jobs”. From the perspective of the European Union, job quality can be defined along two distinct dimensions. First, while the internationally agreed definition is rather static (e.g. related to the current conditions of the worker), the emerging interpretation at the EU level incorporates the extent to which a given job leads to nurturing human capital, and thereby empowering workers with more skills and well-being over time. Second, job quality can be seen from a “micro” perspective, which only accounts for the condition of the individual worker; or from a more “macro” perspective, which considers whether the sector in which the job emerges is compatible with the EU’s agenda, and in particular with the twin (green and digital) transition. As a result, we argue that ideally, Europe should avoid creating “good” jobs in “bad” sectors, as well as “bad” jobs in “good” sectors. The ultimate goal is to create “good” jobs in “good” sectors….(More)”

How public money is shaping the future of AI

Curated on Posted on by Stefaan Verhulst

Report by Ethica: “The European Union aims to become the “home of trustworthy Artificial Intelligence” and has committed the biggest existing public funding to invest in AI over the next decade. However, the lack of accessible data and comprehensive reporting on the Framework Programmes’ results and impact hinder the EU’s capacity to achieve its objectives and undermine the credibility of its commitments. 

This research commissioned by the European AI & Society Fund, recommends publicly accessible data, effective evaluation of the real-world impacts of funding, and mechanisms for civil society participation in funding before investing further public funds to achieve the EU’s goal of being the epicenter of trustworthy AI.

Among its findings, the research has highlighted the negative impact of the European Union’s investment in artificial intelligence (AI). The EU invested €10bn into AI via its Framework Programmes between 2014 and 2020, representing 13.4% of all available funding. However, the investment process is top-down, with little input from researchers or feedback from previous grantees or civil society organizations. Furthermore, despite the EU’s aim to fund market-focused innovation, research institutions and higher and secondary education establishments received 73% of the total funding between 2007 and 2020. Germany, France, and the UK were the largest recipients, receiving 37.4% of the total EU budget.

The report also explores the lack of commitment to ethical AI, with only 30.3% of funding calls related to AI mentioning trustworthiness, privacy, or ethics. Additionally, civil society organizations are not involved in the design of funding programs, and there is no evaluation of the economic or societal impact of the funded work. The report calls for political priorities to align with funding outcomes in specific, measurable ways, citing transport as the most funded sector in AI despite not being an EU strategic focus, while programs to promote SME and societal participation in scientific innovation have been dropped….(More)”.