LGBTQ+ data availability

Curated on Posted on by Stefaan Verhulst

Report by Beyond Deng and Tara Watson: “LGBTQ+ (Lesbian, Gay, Bisexual, Transgender, Queer/Questioning) identification has doubled over the past decade, yet data on the overall LGBTQ+ population remains limited in large, nationally representative surveys such as the American Community Survey. These surveys are consistently used to understand the economic wellbeing of individuals, but they fail to fully capture information related to one’s sexual orientation and gender identity (SOGI).[1]

Asking incomplete SOGI questions leaves a gap in research that, if left unaddressed, will continue to grow in importance with the increase of the LGBTQ+ population, particularly among younger cohorts. In this report, we provide an overview of four large, nationally representative, and publicly accessible datasets that include information relevant for economic analysis. These include the Behavioral Risk Factor Surveillance System (BRFSS), National Health Interview Survey (NHIS), the American Community Survey (ACS), and the Census Household Pulse Survey. Each survey varies by sample size, sample unit, periodicity, geography, and the SOGI information they collect.[2]

The difference in how these datasets collect SOGI information impacts the estimates of LGBTQ+ prevalence. While we find considerable difference in measured LGBT prevalence across datasets, each survey documents a substantial increase in non-straight identity over time. Figure 1 shows that this is largely driven by young adults, who are increasingly likely to identify as LGBT over almost the past ten years. Using data from NHIS, around 4% of 18–24-year-olds in 2013 identified as LGB, which increased to 9.5% in 2021. Because of the short time horizon in these surveys, it is unclear how the current young adult cohort will identify as they age. Despite this, an important takeaway is that younger age groups clearly represent a substantial portion of the LGB community and are important to incorporate in economic analyses…(More)”.

AI in Hiring and Evaluating Workers: What Americans Think

Curated on Posted on by Stefaan Verhulst

Pew Research Center survey: “… finds crosscurrents in the public’s opinions as they look at the possible uses of AI in workplaces. Americans are wary and sometimes worried. For instance, they oppose AI use in making final hiring decisions by a 71%-7% margin, and a majority also opposes AI analysis being used in making firing decisions. Pluralities oppose AI use in reviewing job applications and in determining whether a worker should be promoted. Beyond that, majorities do not support the idea of AI systems being used to track workers’ movements while they are at work or keeping track of when office workers are at their desks.

Yet there are instances where people think AI in workplaces would do better than humans. For example, 47% think AI would do better than humans at evaluating all job applicants in the same way, while a much smaller share – 15% – believe AI would be worse than humans in doing that. And among those who believe that bias along racial and ethnic lines is a problem in performance evaluations generally, more believe that greater use of AI by employers would make things better rather than worse in the hiring and worker-evaluation process. 

Overall, larger shares of Americans than not believe AI use in workplaces will significantly affect workers in general, but far fewer believe the use of AI in those places will have a major impact on them personally. Some 62% think the use of AI in the workplace will have a major impact on workers generally over the next 20 years. On the other hand, just 28% believe the use of AI will have a major impact on them personally, while roughly half believe there will be no impact on them or that the impact will be minor…(More)”.

Accept All: Unacceptable? 

Curated on Posted on by Stefaan Verhulst

Report by Demos and Schillings: “…sought to investigate how our data footprints are being created and exploited online. It involved an exploratory investigation into how data sharing and data regulation practices are impacting citizens: looking into how individuals’ data footprints are created, what people experience when they want to exercise their data rights, and how they feel about how their data is being used. This was a novel approach, using live case studies as they embarked on a data odyssey in order to understand, in real time, the data challenge people face.

We then held a series of stakeholder roundtables with academics, lawyers, technologists, people working in industry and civil society, which focused on diagnosing the problems and what potential solutions already look like, or could look like in the future, across multiple stakeholder groups….(More)” See also: documentary produced by the project partners, law firm Schillings and the independent consumer data action service Rightly, and TVN, alongside this report, here.

Behavioral Economics: Policy Impact and Future Directions

Curated on Posted on by Stefaan Verhulst

Report from the National Academies of Sciences, Engineering, and Medicine: “Behavioral economics – a field based in collaborations among economists and psychologists – focuses on integrating a nuanced understanding of behavior into models of decision-making. Since the mid-20th century, this growing field has produced research in numerous domains and has influenced policymaking, research, and marketing. However, little has been done to assess these contributions and review evidence of their use in the policy arena.

Behavioral Economics: Policy Impact and Future Directions examines the evidence for behavioral economics and its application in six public policy domains: health, retirement benefits, climate change, social safety net benefits, climate change, education, and criminal justice. The report concludes that the principles of behavioral economics are indispensable for the design of policy and recommends integrating behavioral specialists into policy development within government units. In addition, the report calls for strengthening research methodology and identifies research priorities for building on the accomplishments of the field to date…(More)”.

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)”.