New data laws unveiled to improve public services and boost UK economy by £10 billion

Curated on Posted on by Stefaan Verhulst

(UK) Press Release: “A new Bill which will harness the enormous power of data to boost the UK economy by £10 billion, and free up millions of police and NHS staff hours has been introduced to Parliament today (Wednesday 23rd October).

The Data Use and Access Bill will unlock the secure and effective use of data for the public interest, without adding pressures to the country’s finances. The measures will be central to delivering three of the five Missions to rebuild Britain, set out by the Prime Minister:

  • kickstarting economic growth
  • taking back our streets
  • and building an NHS fit for the future

Some of its key measures include cutting down on bureaucracy for our police officers, so that they can focus on tackling crime rather than being bogged down by admin, freeing up 1.5 million hours of their time a year. It will also make patients’ data easily transferable across the NHS so that frontline staff can make better informed decisions for patients more quickly, freeing up 140,000 hours of NHS staff time every year, speeding up care and improving patients’ health outcomes.

The better use of data under measures in the Bill will also simplify important tasks such as renting a flat and starting work with trusted ways to verify your identity online, or enabling electronic registration of births and deaths, so that people and businesses can get on with their lives without unnecessary admin.

Vital safeguards will remain in place to track and monitor how personal data is used, giving peace of mind to patients and victims of crime. IT systems in the NHS operate to the highest standards of security and all organisations have governance arrangements in place to ensure the safe, legal storage and use of data…(More)”

Make it make sense: the challenge of data analysis in global deliberation

Curated on Posted on by Stefaan Verhulst

Blog by Iñaki Goñi: “From climate change to emerging technologies to economic justice to space, global and transnational deliberation is on the rise. Global deliberative processes aim to bring citizen-centred governance to issues that no single nation can resolve alone. Running deliberative processes at this scale poses a unique set of challenges. How to select participants, make the forums accountable, impactful, fairly designed, and aware of power imbalances, are all crucial and open questions….

Massifying participation will be key to invigorating global deliberation. Assemblies will have a better chance of being seen as legitimate, fair, and publicly supported if they involve thousands or even millions of diverse participants. This raises an operational challenge: how to systematise political ideas from many people across the globe.

In a centralised global assembly, anything from 50 to 500 citizens from various countries engage in a single deliberation and produce recommendations or political actions by crossing languages and cultures. In a distributed assembly, multiple gatherings are convened locally that share a common but flexible methodology, allowing participants to discuss a common issue applied both to local and global contexts. Either way, a global deliberation process demands the organisation and synthesis of possibly thousands of ideas from diverse languages and cultures around the world.

How could we ever make sense of all that data to systematise citizens’ ideas and recommendations? Most people turn their heads to computational methods to help reduce complexity and identify patterns. First up, one technique for analysing text amounts to little more than simple counting, through which we can produce something like a frequency table or a wordcloud…(More)”.

Open government data and self-efficacy: The empirical evidence of micro foundation via survey experiments

Curated on Posted on by Stefaan Verhulst

Paper by Kuang-Ting Tai, Pallavi Awasthi, and Ivan P. Lee: “Research on the potential impacts of government openness and open government data is not new. However, empirical evidence regarding the micro-level impact, which can validate macro-level theories, has been particularly limited. Grounded in social cognitive theory, this study contributes to the literature by empirically examining how the dissemination of government information in an open data format can influence individuals’ perceptions of self-efficacy, a key predictor of public participation. Based on two rounds of online survey experiments conducted in the U.S., the findings reveal that exposure to open government data is associated with decreased perceived self-efficacy, resulting in lower confidence in participating in public affairs. This result, while contrary to optimistic assumptions, aligns with some other empirical studies and highlights the need to reconsider the format for disseminating government information. The policy implications suggest further calibration of open data applications to target professional and skilled individuals. This study underscores the importance of experiment replication and theory development as key components of future research agendas…(More)”.

Nature-rich nations push for biodata payout

Curated on Posted on by Stefaan Verhulst

Article by Lee Harris: “Before the current generation of weight-loss drugs, there was hoodia, a cactus that grows in southern Africa’s Kalahari Desert, and which members of the region’s San tribe have long used to stave off hunger. UK-based Phytopharm licensed the active ingredient in the cactus in 1996, and made numerous attempts to commercialise weight-loss products derived from it.

The company won licensing deals with Pfizer and Unilever, but drew outrage from campaigners who argued that the country was ripping off indigenous groups that had made the discovery. Indignation grew after the chief executive said it could not compensate local tribes because “the people who discovered the plant have disappeared”. (They had not).

This is just one example of companies using biological resources discovered in other countries for financial gain. The UN has attempted to set fairer terms with treaties such as the 1992 Convention on Biological Diversity, which deals with the sharing of genetic resources. But this approach has been seen by many developing countries as unsatisfactory. And earlier tools governing trade in plants and microbes may become less useful as biological data is now frequently transmitted in the form of so-called digital sequence information — the genetic code derived from those physical resources.

Now, the UN is working on a fund to pay stewards of biodiversity — notably communities in lower-income countries — for discoveries made with genetic data from their ecosystems. The mechanism was established in 2022 as part of the Conference of Parties to the UN Convention on Biological Diversity, a sister process to the climate “COP” initiative. But the question of how it will be governed and funded will be on the table at the October COP16 summit in Cali, Colombia.

If such a fund comes to fruition — a big “if” — it could raise billions for biodiversity goals. The sectors that depend on this genetic data — notably, pharmaceuticals, biotech and agribusiness — generate revenues exceeding $1tn annually, and African countries plan to push for these sectors to contribute 1 per cent of all global retail sales to the fund, according to Bloomberg.

There’s reason to temper expectations, however. Such a fund would lack the power to compel national governments or industries to pay up. Instead, the strategy is focused around raising ambition — and public pressure — for key industries to make voluntary contributions…(More)”.

The New Artificial Intelligentsia

Curated on Posted on by Stefaan Verhulst

Essay by Ruha Benjamin: “In the Fall of 2016, I gave a talk at the Institute for Advanced Study in Princeton titled “Are Robots Racist?” Headlines such as “Can Computers Be Racist? The Human-Like Bias of Algorithms,” “Artificial Intelligence’s White Guy Problem,” and “Is an Algorithm Any Less Racist Than a Human?” had captured my attention in the months before. What better venue to discuss the growing concerns about emerging technologies, I thought, than an institution established during the early rise of fascism in Europe, which once housed intellectual giants like J. Robert Oppenheimer and Albert Einstein, and prides itself on “protecting and promoting independent inquiry.”

My initial remarks focused on how emerging technologies reflect and reproduce social inequities, using specific examples of what some termed “algorithmic discrimination” and “machine bias.” A lively discussion ensued. The most memorable exchange was with a mathematician who politely acknowledged the importance of the issues I raised but then assured me that “as AI advances, it will eventually show us how to address these problems.” Struck by his earnest faith in technology as a force for good, I wanted to sputter, “But what about those already being harmed by the deployment of experimental AI in healthcare, education, criminal justice, and more—are they expected to wait for a mythical future where sentient systems act as sage stewards of humanity?”

Fast-forward almost 10 years, and we are living in the imagination of AI evangelists racing to build artificial general intelligence (AGI), even as they warn of its potential to destroy us. This gospel of love and fear insists on “aligning” AI with human values to rein in these digital deities. OpenAI, the company behind ChatGPT, echoed the sentiment of my IAS colleague: “We are improving our AI systems’ ability to learn from human feedback and to assist humans at evaluating AI. Our goal is to build a sufficiently aligned AI system that can help us solve all other alignment problems.” They envision a time when, eventually, “our AI systems can take over more and more of our alignment work and ultimately conceive, implement, study, and develop better alignment techniques than we have now. They will work together with humans to ensure that their own successors are more aligned with humans.” For many, this is not reassuring…(More)”.

The Critical Role of Questions in Building Resilient Democracies

Curated on Posted on by Stefaan Verhulst

Article by Stefaan G. Verhulst, Hannah Chafetz, and Alex Fischer: “Asking questions in new and participatory ways can complement advancements in data science and AI while enabling more inclusive and more adaptive democracies…

Yet a crisis, as the saying goes, always contains kernels of opportunity. Buried within our current dilemma—indeed, within one of the underlying causes of it—is a potential solution. Democracies are resilient and adaptive, not static. And importantly, data and artificial intelligence (AI), if implemented responsibly, can contribute to making them more resilient. Technologies such as AI-supported digital public squares and crowd-sourcing are examples of how generative AI and large language models can improve community connectivity, societal health, and public services. Communities can leverage these tools for democratic participation and democratizing information. Through this period of technological transition, policy makers and communities are imagining how digital technologies can better engage our collective intelligence…

Achieving this requires new tools and approaches, specifically the collective process of asking better questions.

Formulated inclusively, questions help establish shared priorities and impart focus, efficiency, and equity to public policy. For instance, school systems can identify indicators and patterns of experiences, such as low attendance rates, that signal a student is at risk of not completing school. However, they rarely ask the positive outlier question of what enables some at-risk students to overcome challenges and finish school. Is it a good teacher relationship, an after-school program, the support of a family member, or a combination of these and other factors? Asking outlier (and orphan, or overlooked and neglected) questions can help refocus programs and guide policies toward areas with the highest potential for impact.

Not asking the right questions can also have adverse effects. For example, many city governments have not asked whether and how people of different genders, in different age groups, or with different physical mobility needs experience local public transportation systems. Creating the necessary infrastructure for people with a variety of needs to travel safely and efficiently increases health and well-being. Questions like whether sidewalks are big enough for strollers and whether there is sufficient public transport near schools can help spotlight areas for improvement, and show where age- or gender-disaggregated data is needed most…(More)”.

G7 Toolkit for Artificial Intelligence in the Public Sector

Curated on Posted on by Stefaan Verhulst

Toolkit by OECD: “…a comprehensive guide designed to help policymakers and public sector leaders translate principles for safe, secure, and trustworthy Artificial Intelligence (AI) into actionable policies. AI can help improve the efficiency of internal operations, the effectiveness of policymaking, the responsiveness of public services, and overall transparency and accountability. Recognising both the opportunities and risks posed by AI, this toolkit provides practical insights, shares good practices for the use of AI in and by the public sector, integrates ethical considerations, and provides an overview of G7 trends. It further showcases public sector AI use cases, detailing their benefits, as well as the implementation challenges faced by G7 members, together with the emerging policy responses to guide and coordinate the development, deployment, and use of AI in the public sector. The toolkit finally highlights key stages and factors characterising the journey of public sector AI solutions…(More)”

How elderly dementia patients are unwittingly fueling political campaigns

Curated on Posted on by Stefaan Verhulst

Article by Blake Ellis, et al: “The 80-year-old communications engineer from Texas had saved for decades, driving around in an old car and buying clothes from thrift stores so he’d have enough money to enjoy his retirement years.

But as dementia robbed him of his reasoning abilities, he began making online political donations over and over again — eventually telling his son he believed he was part of a network of political operatives communicating with key Republican leaders. In less than two years, the man became one of the country’s largest grassroots supporters of the Republican Party, ultimately giving away nearly half a million dollars to former President Donald Trump and other candidates. Now, the savings account he spent his whole life building is practically empty.

The story of this unlikely political benefactor is one of many playing out across the country.

More than 1,000 reports filed with government agencies and consumer advocacy groups reviewed by CNN, along with an analysis of campaign finance data and interviews with dozens of contributors and their family members, show how deceptive political fundraisers have victimized hundreds of elderly Americans and misled those battling dementia or other cognitive impairments into giving away millions of dollars — far more than they ever intended. Some unintentionally joined the ranks of the top grassroots political donors in the country as they tapped into retirement savings and went into debt, contributing six-figure sums through thousands of transactions…(More)”.

Long-term validation of inner-urban mobility metrics derived from Twitter/X

Curated on Posted on by Stefaan Verhulst

Paper by Steffen Knoblauch et al: “Urban mobility analysis using Twitter as a proxy has gained significant attention in various application fields; however, long-term validation studies are scarce. This paper addresses this gap by assessing the reliability of Twitter data for modeling inner-urban mobility dynamics over a 27-month period in the. metropolitan area of Rio de Janeiro, Brazil. The evaluation involves the validation of Twitter-derived mobility estimates at both temporal and spatial scales, employing over 1.6 × 1011 mobile phone records of around three million users during the non-stationary mobility period from April 2020 to. June 2022, which coincided with the COVID-19 pandemic. The results highlight the need for caution when using Twitter for short-term modeling of urban mobility flows. Short-term inference can be influenced by Twitter policy changes and the availability of publicly accessible tweets. On the other hand, this long-term study demonstrates that employing multiple mobility metrics simultaneously, analyzing dynamic and static mobility changes concurrently, and employing robust preprocessing techniques such as rolling window downsampling can enhance the inference capabilities of Twitter data. These novel insights gained from a long-term perspective are vital, as Twitter – rebranded to X in 2023 – is extensively used by researchers worldwide to infer human movement patterns. Since conclusions drawn from studies using Twitter could be used to inform public policy, emergency response, and urban planning, evaluating the reliability of this data is of utmost importance…(More)”.

Veridical Data Science

Curated on Posted on by Stefaan Verhulst

Book by Bin Yu and Rebecca L. Barter: “Most textbooks present data science as a linear analytic process involving a set of statistical and computational techniques without accounting for the challenges intrinsic to real-world applications. Veridical Data Science, by contrast, embraces the reality that most projects begin with an ambiguous domain question and messy data; it acknowledges that datasets are mere approximations of reality while analyses are mental constructs.
Bin Yu and Rebecca Barter employ the innovative Predictability, Computability, and Stability (PCS) framework to assess the trustworthiness and relevance of data-driven results relative to three sources of uncertainty that arise throughout the data science life cycle: the human decisions and judgment calls made during data collection, cleaning, and modeling. By providing real-world data case studies, intuitive explanations of common statistical and machine learning techniques, and supplementary R and Python code, Veridical Data Science offers a clear and actionable guide for conducting responsible data science. Requiring little background knowledge, this lucid, self-contained textbook provides a solid foundation and principled framework for future study of advanced methods in machine learning, statistics, and data science…(More)”.