Selected Readings on Digital Self-Determination for Migrants

Curated on Posted on by Uma

By Uma Kalkar, Marine Ragnet, and Stefaan Verhulst

Digital self-determination (DSD) is a multidisciplinary concept that extends self-determination to the digital sphere. Self-determination places humans (and their ability to make ‘moral’ decisions) at the center of decision-making actions. While self-determination is considered as a jus cogens rule (i.e. a global norm), the concept of digital self-determination came only to light in the early 2010s as a result of the increasing digitization of most aspects of society. 

While digitalization has opened up new opportunities for self-expression and communication for individuals across the globe, its reach and benefits have not been evenly distributed. For instance, migrants and refugees are particularly vulnerable to the deepening inequalities and power structures brought on by increased digitization, and the subsequent datafication. Further, non-traditional data, such as social media and telecom data, have brought great potential to improve our understanding of the migration experience and patterns of mobility that can provide more targeted migration policies and services yet it also has brought new concerns related to the lack of agency to determine how the data is being used and who determines the migration narrative.

These selected readings look at DSD in light of the growing ubiquity of technology applications and specifically focus on their impacts on migrants. They were produced to inform the first studio on DSD and migration co-hosted by the Big Data for Migration Alliance and the International Digital Self Determination Network. The readings are listed in alphabetical order.

These readings serve as a primer to offer base perspectives on DSD and its manifestations, as well as provide a better understanding of how migration data is managed today to advance or hinder life for those on the move. Please alert us of any other publication we should include moving forward.

Berens, Jos, Nataniel Raymond, Gideon Shimshon, Stefaan Verhulst, and Lucy Bernholz. “The Humanitarian Data Ecosystem: the Case for Collective Responsibility.” Stanford Center for Philanthropy and Civil Society, 2017.

  • The authors explore the challenges to, and potential solutions for, the responsible use of digital data in the context of international humanitarian action. Data governance is related to DSD because it oversees how the information extracted from an individual—understood by DSD as an extension of oneself in the digital sphere—is handled.
  • They argue that in the digital age, the basic service provision activities of NGOs and aid organizations have become data collection processes. However, the ecosystem of actors is “uncoordinated” creating inefficiencies and vulnerabilities in the humanitarian space.
  • The paper presents a new framework for responsible data use in the humanitarian domain. The authors advocate for data users to follow three steps: 
  1. “[L]ook beyond the role they take up in the ‘data-lifecycle’ and consider previous and following steps and roles;
  2. Develop sound data responsibility strategies not only to prevent harm to their own operations but also to other organizations in the ‘data-lifecycle;’ and, 
  3. Collaborate with and learn from other organizations, both in the humanitarian field and beyond, to establish broadly supported guidelines and standards for humanitarian data use.”

Currion, Paul. “The Refugee Identity.” Caribou Digital (via Medium), March 13, 2018.

  • Developed as part of a DFID-funded initiative, this essay outlines the Data Requirements for Service Delivery within Refugee Camps project that investigated current data standards and design of refugee identity systems.
  • Currion finds that since “the digitisation of aid has already begun…aid agencies must therefore pay more attention to the way in which identity systems affect the lives and livelihoods of the forcibly displaced, both positively and negatively.” He argues that an interoperable digital identity for refugees is essential to access financial, social, and material resources while on the move but also to tap into IoT services.
  • However, many refugees are wary of digital tracking and data collection services that could further marginalize them as they search for safety. At present, there are no sector-level data standards around refugee identity data collection, combination, and centralization. How can regulators balance data protection with government and NGO requirements to serve refugees in the ways they want to uphold their DSD?
  • Currion argues that a Responsible Data approach, as opposed to a process defined by a Data Minimization principle, provides “useful guidelines” but notes that data responsibility “still needs to be translated into organizational policy, then into institutional processes, and finally into operational practice. He further adds that “the digitization of aid, if approached from a position that empowers the individual as much as the institution, offers a chance to give refugees back their voices.”

Decker, Rianne, Paul Koot, S. Ilker Birbil, Mark van Embden Andres. “Co-designing algorithms for governance: Ensuring responsible and accountable algorithmic management of refugee camp supplies” Big Data and Society, April 2022. 

  • While recent literature has looked at the negative impacts of big data and algorithms in public governance, claiming they may reinforce existing biases and defy scrutiny by public officials, this paper argues that designing algorithms with relevant government and society stakeholders might be a way to make them more accountable and transparent. 
  • It presents a case study of the development of an algorithmic tool to estimate the populations of refugee camps to manage the delivery of emergency supplies. The algorithms included in this tool were co-designed with relevant stakeholders. 
  • This may provide a way to uphold DSD by  contributing to the “accountability of the algorithm by making the estimations transparent and explicable to its users.”
  • The authors found that the co-design process enabled better accuracy and responsibility and fostered collaboration between partners, creating a suitable purpose for the tool and making the algorithm understandable to its users. This enabled algorithmic accountability. 
  • The authors note, however, that the beneficiaries of the tools were not included in the design process, limiting the legitimacy of the initiative. 

European Migration Network. “The Use of Digitalisation and Artificial Intelligence in Migration Management.” EMN-OECD Inform Series, February 2022.

  • This paper explores the role of new digital technologies in the management of migration and asylum, focusing specifically on where digital technologies, such as online portals, blockchain, and AI-powered speech and facial recognition systems are being used across Europe to navigate the processes of obtaining visas, claiming asylum, gaining citizenship,  and deploying border control management. 
  • Further, it points to friction between GDPR and new technologies like blockchain—which by decision does not allow for the right to be forgotten—and potential workarounds, such as two-step pseudonymisation.
  • As well, it highlights steps taken to oversee and open up data protection processes for immigration. Austria, Belgium, and France have begun to conduct Data Protection Impact Assessments; France has a portal that allows one to request the right to be forgotten; Ireland informs online service users on how data can be shared or used with third-party agencies; and Spain outlines which personal data are used in immigration as per the Registry Public Treatment Activities.
  • Lastly, the paper points out next steps for policy development that upholds DSD, including universal access and digital literacy, trust in digital systems, willingness for government digital transformations, and bias and risk reduction.

Martin, Aaron, Gargi Sharma, Siddharth Peter de Souza, Linnet Taylor, Boudewijn van Eerd, Sean Martin McDonald, Massimo Marelli, Margie Cheesman, Stephan Scheel, and Huub Dijstelbloem. “Digitisation and Sovereignty in Humanitarian Space: Technologies, Territories and Tensions.” Geopolitics (2022): 1-36.

  • This paper explores how digitisation and datafication are reshaping sovereign authority, power, and control in humanitarian spaces.
  • Building on the notion that technology is political, Martin et al. discuss three cases where digital tools powered by partnerships between international organizations and NGOs and private firms such as Palantir and Facebook have raised concerns for data to be “repurposed” to undermine national sovereignty and distort humanitarian aims with for-profit motivations.
  • The authors draw attention to how cyber dependencies threaten international humanitarian organizations’ purported digital sovereignty. They touch on the tensions between national and digital sovereignty and self-governance.
  • The paper further argues that the rise of digital technologies in the governance of international mobility and migration policies “has all kinds of humanitarian and security consequences,” including (but not limited to) surveillance, privacy infringement, profiling, selection, inclusion/exclusion, and access barriers. Specifically, Scheel introduces the notion of function creep—the use of digital data beyond initially defined purposes—and emphasizes its common use in the context of migration as part “of the modus operandi of sovereign power.”

McAuliffe, Marie, Jenna Blower, and Ana Beduschi. “Digitalization and Artificial Intelligence in Migration and Mobility: Transnational Implications of the COVID-19 Pandemic.” Societies 11, no. 135 (2021): 1-13.

  • This paper critically examines the implications of intensifying digitalization and AI for migration and mobility systems in a post- COVID transnational context. 
  • The authors first situate digitalization and AI in migration by analyzing its uptake throughout the Migration Cycle, i.e. to verify identities and visas, “enable “smart” border processing,” and understand travelers’ adherence to legal frameworks. It then evaluates the current challenges and opportunities to migrants and migration systems brought about by deepening digitalization due to COVID-19. For example, contact tracing, infection screening, and quarantining procedures generate increased data about an individual and are meant, by design, to track and trace people, which raises concerns about migrants’ safety, privacy, and autonomy.
  • This essay argues that recent changes show the need for further computational advances that incorporate human rights throughout the design and development stages, “to mitigate potential risks to migrants’ human rights.” AI is severely flawed when it comes to decision-making around minority groups because of biased training data and could further marginalize vulnerable populations and intrusive data collection for public health could erode the power of one’s universal right to privacy. Leaving migrants at the mercy of black-box AI systems fails to uphold their right to DSD because it forces them to relinquish their agency and power to an opaque system.

Ponzanesi, Sandra. “Migration and Mobility in a Digital Age: (Re)Mapping Connectivity and Belonging.” Television & New Media 20, no. 6 (2019): 547-557.

  • This article explores the role of new media technologies in rethinking the dynamics of migration and globalization by focusing on the role of migrant users as “connected” and active participants, as well as “screened” and subject to biometric datafication, visualization, and surveillance.
  • Elaborating on concepts such as “migration” and “mobility,” the article analyzes the paradoxes of intermittent connectivity and troubled belonging, which are seen as relational definitions that are always fluid, negotiable, and porous.
  • It states that a city’s digital infrastructures are “complex sociotechnical systems” that have a functional side related to access and connectivity and a performative side where people engage with technology. Digital access and action represent areas of individual and collective manifestations of DSD. For migrants, gaining digital access and skills and “enacting citizenship” are important for resettlement. Ponzanesi advocates for further research conducted both from the bottom-up that leans on migrant experiences with technology to resettle and remain in contact with their homeland and a top-down approach that looks at datafication, surveillance, digital/e-governance as a part of the larger technology application ecosystem to understand contemporary processes and problems of migration.

Remolina, Nydia, and Mark James Findlay. “The Paths to Digital Self-Determination — A Foundational Theoretical Framework.” SMU Centre for AI & Data Governance Research Paper No. 03 (2021): 1-34.

  • Remolina and Findlay stress that self-determination is the vehicle by which people “decide their own destiny in the international order.” Decision-making ability powers humans to be in control of their own lives and excited to pursue a set of actions. Collective action, or the ability to make decisions as a part of a group—be it based on ethnicity, nationality, shared viewpoints, etc.—further motivates oneself.
  • The authors discuss how the European Union and European Court of Human Rights’ “principle of subsidiarity” aligns with self-determination because it advocates for power to be placed at the lowest level possible to preserve bottom-up agency with a “reasonable level of efficiency.” In practice, the results of subsidiarity have been disappointing.
  • The paper provides examples of indigenous populations’ fight for self-determination, offline and online. Here, digital self-determination refers to the challenges indigenous peoples face in accessing growing government uses of technology for unlocking innovative solutions because of a lack of physical infrastructure due to structural and social inequities between settler and indigenous communities.
  • Understanding self-determination—and by extension, digital self-determination as a human right, the report investigates how autonomy, sovereignty, the legal definition of a ‘right,’ inclusion, agency, data governance, data ownership, data control, and data quality.
  • Lastly, the paper presents a foundational theoretical framework that goes beyond just protecting personal data and privacy. Understanding that DSD “cannot be detached from duties for responsible data use,” the authors present a collective and individual dimension to DSD. They extend the individual dimension of DSD to include both my data and data about me that can be used to influence a person’s actions through micro-targeting and nudge techniques. They update the collective dimension of DSD to include the views and influences of organizations, businesses, and communities online and call for a better way of visualizing the ‘social self’ and its control over data.

Ziebart, Astrid, and Jessica Bither. “AI, Digital Identities, Biometrics, Blockchain: A Primer on the Use of Technology in Migration Management.” Migration Strategy Group on International Cooperation and Development, June 2020.

  • Ziebart and Bither note the implications of increasingly sophisticated use of technology and data collection by governments with respect to their citizens. They note that migrants and refugees “often are exposed to particular vulnerabilities” during these processes and underscore the need to bring migrants into data gathering and use policy conversations.  
  • The authors discuss the promise of technology—i.e., to predict migration through AI-powered analyses, employ technologies to reduce friction in the asylum-seeking processes, and the power of digital identities for those on the move. However, they stress the need to combine these tools with informational self-determination that allows migrants to own and control what data they share and how and where the data are used.
  • The migration and refugee policy space faces issues of “tech evangelism,” where technologies are being employed just because they exist, rather than because they serve an actual policy need or provide an answer to a particular policy question. This supply-driven policy implementation signals the need for more migrant voices to inform policymakers on what tools are actually useful for the migratory experience. In order to advance the digital agency of migrants, the paper offers recommendations for some of the ethical challenges these technologies might pose and ultimately advocates for greater participation of migrants and refugees in devising technology-driven policy instruments for migration issues.

On-the-go interesting resources 

  • Empowering Digital Self-Determination, mediaX at Stanford University: This short video presents definitions of DSD, and digital personhood, identity, and privacy and an overview of their applications across ethics, law, and the private sector.
  • Digital Self-Determination — A Living Syllabus: This syllabus and assorted materials have been created and curated from the 2021 Research Sprint run by the Digital Asia Hub and Berkman Klein Center for Internet Society at Harvard University. It introduces learners to the fundamentals of DSD across a variety of industries to enrich understanding of its existing and potential applications.
  • Digital Self-Determination Wikipedia Page: This Wikipedia page was developed by the students who took part in the Berkman Klein Center research sprint on digital self-determination. It provides a comprehensive overview of DSD definitions and its key elements, which include human-centered design, robust privacy mandates and data governance, and control over data use to give data subjects the ability to choose how algorithms manipulate their data for autonomous decision-making.
  • Roger Dubach on Digital Self-Determination: This short video presents DSD in the public sector and the dangers of creating a ‘data-protected’ world, but rather on understanding how governments can efficiently use data and protect privacy. Note: this video is part of the Living Syllabus course materials (Digital Self-Determination/Module 1: Beginning Inquiries).

Responsiveness of open innovation to COVID-19 pandemic: The case of data for good

Curated on Posted on by Stefaan Verhulst

Paper by Francesco Scotti, Francesco Pierri, Giovanni Bonaccorsi, and Andrea Flori: “Due to the COVID-19 pandemic, countries around the world are facing one of the most severe health and economic crises of recent history and human society is called to figure out effective responses. However, as current measures have not produced valuable solutions, a multidisciplinary and open approach, enabling collaborations across private and public organizations, is crucial to unleash successful contributions against the disease. Indeed, the COVID-19 represents a Grand Challenge to which joint forces and extension of disciplinary boundaries have been recognized as main imperatives. As a consequence, Open Innovation represents a promising solution to provide a fast recovery. In this paper we present a practical application of this approach, showing how knowledge sharing constitutes one of the main drivers to tackle pressing social needs. To demonstrate this, we propose a case study regarding a data sharing initiative promoted by Facebook, the Data For Good program. We leverage a large-scale dataset provided by Facebook to the research community to offer a representation of the evolution of the Italian mobility during the lockdown. We show that this repository allows to capture different patterns of movements on the territory with increasing levels of detail. We integrate this information with Open Data provided by the Lombardy region to illustrate how data sharing can also provide insights for private businesses and local authorities. Finally, we show how to interpret Data For Good initiatives in light of the Open Innovation Framework and discuss the barriers to adoption faced by public administrations regarding these practices…(More)”.

Information aggregation and collective intelligence beyond the wisdom of crowds

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Paper by Tatsuya Kameda, Wataru Toyokawa & R. Scott Tindale: “In humans and other gregarious animals, collective decision-making is a robust behavioural feature of groups. Pooling individual information is also fundamental for modern societies, in which digital technologies have exponentially increased the interdependence of individual group members. In this Review, we selectively discuss the recent human and animal literature, focusing on cognitive and behavioural mechanisms that can yield collective intelligence beyond the wisdom of crowds. We distinguish between two group decision-making situations: consensus decision-making, in which a group consensus is required, and combined decision-making, in which a group consensus is not required. We show that in both group decision-making situations, cognitive and behavioural algorithms that capitalize on individual heterogeneity are the key for collective intelligence to emerge. These algorithms include accuracy or expertise-weighted aggregation of individual inputs and implicit or explicit coordination of cognition and behaviour towards division of labour. These mechanisms can be implemented either as ‘cognitive algebra’, executed mainly within the mind of an individual or by some arbitrating system, or as a dynamic behavioural aggregation through social interaction of individual group members. Finally, we discuss implications for collective decision-making in modern societies characterized by a fluid but auto-correlated flow of information and outline some future directions….(More)”.

Innovation Indicators

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Paper by Fred Gault and Luc Soete: “Innovation indicators support research on innovation and the development of innovation policy. Once a policy has been implemented, innovation indicators can be used to monitor and evaluate the result, leading to policy learning. Producing innovation indicators requires an understanding of what innovation is. There are many definitions in the literature, but innovation indicators are based on statistical measurement guided by international standard definitions of innovation and of innovation activities.

Policymakers are not just interested in the occurrence of innovation but in the outcome. Does it result in more jobs and economic growth? Is it expected to reduce carbon emissions, to advance renewable energy production and energy storage? How does innovation support the Sustainable Development Goals? From the innovation indicator perspective, innovation can be identified in surveys, but that only shows that there is, or there is not, innovation. To meet specific policy needs, a restriction can be imposed on the measurement of innovation. The population of innovators can be divided into those meeting the restriction, such as environmental improvements, and those that do not. In the case of innovation indicators that show a change over time, such as “inclusive innovation,” there may have to be a baseline measurement followed by a later measurement to see if inclusiveness is present, or growing, or not. This may involve social as well as institutional surveys. Once the innovation indicators are produced, they can be made available to potential users through databases, indexes, and scoreboards. Not all of these are based on the statistical measurement of innovation. Some use proxies, such as the allocation of financial and human resources to research and development, or the use of patents and academic publications. The importance of the databases, indexes, and scoreboards is that the findings may be used for the ranking of “innovation” in participating countries, influencing their behavior. While innovation indicators have always been influential, they have the potential to become more so. For decades, innovation indicators have focused on innovation in the business sector, while there have been experiments on measuring innovation in the public (general government sector and public institutions) and the household sectors. Historically, there has been no standard definition of innovation applicable in all sectors of the economy (business, public, household, and non-profit organizations serving households sectors). This changed with the Oslo Manual in 2018, which published a general definition of innovation applicable in all economic sectors. Applying a general definition of innovation has implications for innovation indicators and for the decisions that they influence. If the general definition is applied to the business sector, it includes product innovations that are made available to potential users rather than being introduced on the market. The product innovation can be made available at zero price, which has influence on innovation indicators that are used to describe the digital transformation of the economy. The general definition of innovation, the digital transformation of the economy, and the growing importance of zero price products influence innovation indicators…(More)”.

The digitalisation of agriculture: A literature review and emerging policy issues

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OECD Working Paper: “Digitalisation offers the potential to help address the productivity, sustainability and resilience challenges facing agriculture. Evidence on the adoption and impacts of digital agriculture in OECD countries from national surveys and the literature indicates broad use of digital technologies in row crop farms, but less evidence is available on uptake for livestock and speciality crops. Common barriers to adoption include costs (up-front investment and recurring maintenance expenses), relevance and limited use cases, user-friendliness, high operator skill requirements, mistrust of algorithms, and technological risk. National governments have an important role in addressing bottlenecks to adoption, such as by ensuring better information about costs and benefits of various technologies (including intangible benefits such as quality of life improvements); investing in human capital; ensuring appropriate incentives for innovation; serving as knowledge brokers and facilitators of data-sharing to spur inclusive, secure and representative data ecosystems; and promoting competitive markets….(More)”.

Radically Human: How New Technology Is Transforming Business and Shaping Our Future

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Book by Paul Daugherty and H. James Wilson: “Technology advances are making tech more . . . human. This changes everything you thought you knew about innovation and strategy. In their groundbreaking book, “Human + Machine,” Accenture technology leaders Paul R. Daugherty and H. James Wilson showed how leading organizations use the power of human-machine collaboration to transform their processes and their bottom lines. Now, as new AI powered technologies like the metaverse, natural language processing, and digital twins begin to rapidly impact both life and work, those companies and other pioneers across industries are tipping the balance even more strikingly toward the human side with technology-led strategy that is reshaping the very nature of innovation. In “Radically Human,” Daugherty and Wilson show this profound shift, fast-forwarded by the pandemic, toward more human–and more humane–technology. Artificial intelligence is becoming less artificial and more intelligent. Instead of data-hungry approaches to AI, innovators are pursuing data-efficient approaches that enable machines to learn as humans do. Instead of replacing workers with machines, they’re unleashing human expertise to create human-centered AI. In place of lumbering legacy IT systems, they’re building cloud-first IT architectures able to continuously adapt to a world of billions of connected devices. And they’re pursuing strategies that will take their place alongside classic, winning business formulas like disruptive innovation. These against-the-grain approaches to the basic building blocks of business–Intelligence, Data, Expertise, Architecture, and Strategy (IDEAS)–are transforming competition. Industrial giants and startups alike are drawing on this radically human IDEAS framework to create new business models, optimize post-pandemic approaches to work and talent, rebuild trust with their stakeholders, and show the way toward a sustainable future….(More)”.

The Limitations of Privacy Rights

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Paper by Daniel J. Solove: “Individual privacy rights are often at the heart of information privacy and data protection laws. The most comprehensive set of rights, from the European Union’s General Data Protection Regulation (GDPR), includes the right to access, right to rectification (correction), right to erasure, right to restriction, right to data portability, right to object, and right to not be subject to automated decisions. Privacy laws around the world include many of these rights in various forms.

In this article, I contend that although rights are an important component of privacy regulation, rights are often asked to do far more work than they are capable of doing. Rights can only give individuals a small amount of power. Ultimately, rights are at most capable of being a supporting actor, a small component of a much larger architecture. I advance three reasons why rights cannot serve as the bulwark of privacy protection. First, rights put too much onus on individuals when many privacy problems are systematic. Second, individuals lack the time and expertise to make difficult decisions about privacy, and rights cannot practically be exercised at scale with the number of organizations than process people’s data. Third, privacy cannot be protected by focusing solely on the atomistic individual. The personal data of many people is interrelated, and people’s decisions about their own data have implications for the privacy of other people.

The main goal of providing privacy rights aims to provide individuals with control over their personal data. However, effective privacy protection involves not just facilitating individual control, but also bringing the collection, processing, and transfer of personal data under control. Privacy rights are not designed to achieve the latter goal; and they fail at the former goal.

After discussing these overarching reasons why rights are insufficient for the oversized role they currently play in privacy regulation, I discuss the common privacy rights and why each falls short of providing significant privacy protection. For each right, I propose broader structural measures that can achieve its underlying goals in a more systematic, rigorous, and less haphazard way…(More)”.

Transparency of open data ecosystems in smart cities: Definition and assessment of the maturity of transparency in 22 smart cities

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Paper by Martin Lnenicka et al: “This paper focuses on the issue of the transparency maturity of open data ecosystems seen as the key for the development and maintenance of sustainable, citizen-centered, and socially resilient smart cities. This study inspects smart cities’ data portals and assesses their compliance with transparency requirements for open (government) data. The expert assessment of 34 portals representing 22 smart cities, with 36 features, allowed us to rank them and determine their level of transparency maturity according to four predefined levels of maturity – developing, defined, managed, and integrated. In addition, recommendations for identifying and improving the current maturity level and specific features have been provided. An open data ecosystem in the smart city context has been conceptualized, and its key components were determined. Our definition considers the components of the data-centric and data-driven infrastructure using the systems theory approach. We have defined five predominant types of current open data ecosystems based on prevailing data infrastructure components. The results of this study should contribute to the improvement of current data ecosystems and build sustainable, transparent, citizen-centered, and socially resilient open data-driven smart cities…(More)”.

Governing AI to Advance Shared Prosperity

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Chapter by Ekaterina Klinova: “This chapter describes a governance approach to promoting AI research and development that creates jobs and advances shared prosperity. Concerns over the labor-saving focus of AI advancement are shared by a growing number of economists, technologists, and policymakers around the world. They warn about the risk of AI entrenching poverty and inequality globally. Yet, translating those concerns into proactive governance interventions that would steer AI away from generating excessive levels of automation remains difficult and largely unattempted. Key causes of this difficulty arise from two types of sources: (1) insufficiently deep understanding of the full composition of factors giving AI R&D its present emphasis on labor-saving applications; and (2) lack of tools and processes that would enable AI practitioners and policymakers to anticipate and assess the impact of AI technologies on employment, wages and job quality. This chapter argues that addressing (2) will require creating worker-participatory means of differentiating between genuinely worker-benefiting AI and worker-displacing or worker-exploiting AI. To contribute to tackling (1), this chapter reviews AI practitioners’ motivations and constraints, such as relevant laws, market incentives, as well as less tangible but still highly influential constraining and motivating factors, including explicit and implicit norms in the AI field, visions of future societal order popular among the field’s members and ways that AI practitioners define goals worth pursuing and measure success. I highlight how each of these factors contributes meaningfully to giving AI advancement its excessive labor-saving emphasis and describe opportunities for governance interventions that could correct that over emphasis….(More)”.

Four ways we can use our collective imagination to improve how society works

Curated on Posted on by Stefaan Verhulst

Article by Geoff Mulgan: “In the first months of the pandemic there was evidence of a strong desire for transformational change in many countries. People wanted to use the crisis to deal with the big unresolved problems of climate change inequality and much more, encouraged, for example, by the very obvious truth that the most essential jobs were often amongst the lowest paid and lowest status. That everyone was affected by the pandemic seemed likely to fuel a more collective spirit, a recognition of how much our lives are intertwined with those of millions of strangers.

Now much of that energy has gone. People are exhausted, expectations have fallen and a return to normality looks acceptable, however inadequate that normality might have been. War in Ukraine has reminded us just how easily the world can go into retreat and that basic values remain under threat. My hope, though, is that as the pandemic fades from view we will return to our shared need for radical imagination about the future, and the transformations ahead.

I have long believed that we have a major problem with imagination: that we can more easily imagine ecological apocalypse or technological advances than improvements in how our society works: better options for health, welfare or neighbourhoods a generation or two from now.

Some of the reasons for this problem are objective. The majority of people no longer expect their children to be better off than them. They have good reasons for their pessimism: stagnant incomes for much of the population, particularly since the financial crisis. But the causes of this pessimism also lie with institutions – our universities have become better at commenting on or analysing the present than designing the future. Our political parties have largely given up on long-term thinking, while our social movements are generally better at arguing against things than proposing. Amazingly, there are now no media outlets that promote new ideas: magazines and newspapers focus instead on commentary.

One symptom of this is how much public debate, even in its progressive forms, is dominated by quite old ideas. Take, for example, the circular economy. The main ideas were first proposed in the 1980s. They guided many projects (including ones I worked on) in the 1990s, got the backing of the Chinese Communist party nearly twenty years ago, and were then ably evangelized by people like Ellen McArthur. Yet they’re still not wholly mainstream…(More)”.