The 4M Roadmap: A Higher Road to Profitability by Using Big Data for Social Good

Curated on Posted on by Stefaan Verhulst

Report by Brennan Lake: “As the private sector faces conflicting pressures to either embrace or shun socially responsible practices, companies with privately held big-data assets must decide whether to share access to their data for public good. While some managers object to data sharing over concerns of privacy and product cannibalization, others launch well intentioned yet short-lived CSR projects that fail to deliver on lofty goals.

By embedding Shared-Value principles into ‘Data-for-Good’ programs, data-rich firms can launch responsible data-sharing initiatives that minimize risk, deliver sustained impact, and improve overall competitiveness in the process.

The 4M Roadmap by Brennan Lake, a Big-Data and Social Impact professional, guides managers to adopt a ‘Data-for-Good’ model that emphasizes four key pillars of value-creation: Mission, Messaging, Methods, and Monetization. Through deep analysis and private-sector case studies, The 4M Roadmap demonstrates how companies can engage in responsible data sharing to benefit society and business alike…(More)”.

Preparing Researchers for an Era of Freer Information

Curated on Posted on by Stefaan Verhulst

Article by Peter W.B. Phillips: “If you Google my name along with “Monsanto,” you will find a series of allegations from 2013 that my scholarly work at the University of Saskatchewan, focused on technological change in the global food system, had been unduly influenced by corporations. The allegations made use of seven freedom of information (FOI) requests. Although leadership at my university determined that my publications were consistent with university policy, the ensuing media attention, I feel, has led some colleagues, students, and partners to distance themselves to avoid being implicated by association.

In the years since, I’ve realized that my experience is not unique. I have communicated with other academics who have experienced similar FOI requests related to genetically modified organisms in the United States, Canada, England, Netherlands, and Brazil. And my field is not the only one affected: a 2015 Union of Concerned Scientists report documented requests in multiple states and disciplines—from history to climate science to epidemiology—as well as across ideologies. In the University of California system alone, researchers have received open records requests related to research on the health effects of toxic chemicals, the safety of abortions performed by clinicians rather than doctors, and the green energy production infrastructure. These requests are made possible by laws that permit anyone, for any reason, to gain access to public agencies’ records.

These open records campaigns, which are conducted by individuals and groups across the political spectrum, arise in part from the confluence of two unrelated phenomena: the changing nature of academic research toward more translational, interdisciplinary, and/or team-based investigations and the push for more transparency in taxpayer-funded institutions. Neither phenomenon is inherently negative; in fact, there are strong advantages for science and society in both trends. But problems arise when scholars are caught between them—affecting the individuals involved and potentially influencing the ongoing conduct of research…(More)”

Assembling Tomorrow

Curated on Posted on by Stefaan Verhulst

Book by Stanford d.school: “…explores how to use readily accessible tools of design to both mend the mistakes of our past and shape our future for the better. It explores the intangibles, the mysterious forces that contribute to the off-kilter feelings of today, and follows up with actionables to help you alter your perspective and find opportunities in these turbulent times. Mixed throughout are histories of the future, short pieces of speculative fiction that illustrate how things go haywire and what might be in store if we don’t set them straight…(More)”.

Exploring Visitor Density Trends in Rest Areas Through Google Maps Data and Data Mining

Curated on Posted on by Stefaan Verhulst

Paper by Marita Prasetyani, R. Rizal Isnanto and Catur Edi Widodo: “Rest areas play a vital role in ensuring the safety and comfort of travelers. This study examines the visitor density at the toll and non-toll rest areas using data mining techniques applied to Google Maps Places data. By utilizing extensive information from Google Maps, the research aims to uncover patterns and trends in visitor behavior and pinpoint peak usage times. The findings can guide improved planning and management of rest areas, thereby enhancing the overall travel experience for road users and further research to determine the location of the new rest area.Understanding patterns or trends in visitor density at rest areas involves analyzing the time of day, location, and other factors influencing the density level. Understanding these trends can provide essential insights for rest area management, infrastructure planning, and the establishment of new rest areas.Data from Google Maps provides an invaluable source of real-time and historical information, enabling accurate and in-depth analysis of visitor behavior.Data mining helps identify relationships not immediately apparent in the data, providing a deeper understanding and supporting data-driven decision-making…(More)”.

The Essential Principle for Appropriate Data Policy of Citizen Science Projects

Curated on Posted on by Stefaan Verhulst

Chapter by Takeshi Osawa: “Citizen science is one of new paradigms of science. This concept features various project forms, participants, and motivations and implies the need for attention to ethical issues for every participant, which frequently includes nonacademics. In this chapter, I address ethical issues associated with citizen science projects that focus on the data treatment rule and demonstrate a concept on appropriate data policy for these projects. First, I demonstrate that citizen science projects tend to include different types of collaboration, which may lead to certain conflicts among participants in terms of data sharing. Second, I propose an idea that could integrate different types of collaboration according to the theory transcend. Third, I take a case of a citizen science project through which transcend occurred and elucidate the difference between ordinal research and citizen science projects, specifically in terms of the goals of these projects and the goals and motivations of participants, which may change. Finally, I proposed one conceptual idea on how the principal investigator (PI) of a citizen science project can establish data policy after assessing the rights of participants. The basic idea is the division and organization of the data policy in a hierarchy for the project and for the participants. Data policy is one of the important items for establishing the appropriate methods for citizen science as new style of science. As such, practice and framing related to data policy must be carefully monitored and reflected on…(More)”.

Top 10 Emerging Technologies to Address Global Challenges

Curated on Posted on by Stefaan Verhulst

World Economic Forum: “The Top 10 Emerging Technologies of 2024 are:

  • 1. AI for scientific discovery: While artificial intelligence (AI) has been used in research for many years, advances in deep learning, generative AI and foundation models are revolutionizing the scientific discovery process. AI will enable researchers to make unprecedented connections and advancements in understanding diseases, proposing new materials, and enhancing knowledge of the human body and mind​​.
  • 2. Privacy-enhancing technologies: Protecting personal privacy while providing new opportunities for global data sharing and collaboration, “synthetic data” is set to transform how information is handled with powerful applications in health-related research.
  • 3. Reconfigurable intelligent surfaces: These innovative surfaces turn ordinary walls and surfaces into intelligent components for wireless communication while enhancing energy efficiency in wireless networks. They hold promise for numerous applications, from smart factories to vehicular networks​​.
  • 4. High-altitude platform stations: Using aircraft, blimps and balloons, these systems can extend mobile network access to remote regions, helping bridge the digital divide for over 2.6 billion people worldwide​​.
  • 5. Integrated sensing and communication: The advent of 6G networks facilitates simultaneous data collection (sensing) and transmission (communication). This enables environmental monitoring systems that help in smart agriculture, environmental conservation and urban planning. Integrated sensing and communication devices also promise to reduce energy and silicon consumption.
  • 6. Immersive technology for the built world: Combining computing power with virtual and augmented reality, these technologies promise rapid improvements in infrastructure and daily systems​. This technology allows designers and construction professionals to check for correspondence between physical and digital models, ensuring accuracy and safety and advancing sustainability.
  • 7. Elastocalorics: As global temperatures rise, the need for cooling solutions is set to soar. Offering higher efficiency and lower energy use, elastocalorics release and absorb heat under mechanical stress, presenting a sustainable alternative to current technologies.
  • 8. Carbon-capturing microbes: Engineered organisms convert emissions into valuable products like biofuels, providing a promising approach to mitigating climate change.
  • 9. Alternative livestock feeds: protein feeds for livestock sourced from single-cell proteins, algae and food waste could offer a sustainable solution for the agricultural industry.
  • 10. Genomics for transplants: The successful implantation of genetically engineered organs into a human marks a significant advancement in healthcare, offering hope to millions awaiting transplants​​…(More)”.

Mission Driven Bureaucrats: Empowering People To Help Government Do Better

Curated on Posted on by Stefaan Verhulst

Book by Dan Honig: “…argues that the performance of our governments can be transformed by managing bureaucrats for their empowerment rather than for compliance. Aimed at public sector workers, leaders, academics, and citizens alike, it contends that public sectors too often rely on a managerial approach that seeks to tightly monitor and control employees, and thus demotivates and repels the mission-motivated. The book suggests that better performance can in many cases come from a more empowerment-oriented managerial approach—which allows autonomy, cultivates feelings of competence, and creates connection to peers and purpose—which allows the mission-motivated to thrive. Arguing against conventional wisdom, the volume argues that compliance often thwarts, rather than enhances, public value—and that we can often get less corruption and malfeasance with less monitoring. It provides a handbook of strategies for managers to introduce empowerment-oriented strategies into their agency. It also describes what everyday citizens can do to support the empowerment of bureaucrats in their governments. Interspersed throughout this book are featured profiles of real-life Mission Driven Bureaucrats, who exemplify the dedication and motivation that is typical of many civil servants. Drawing on original empirical data from a number of countries and the prior work of other scholars from around the globe, the volume argues that empowerment-oriented management and how to cultivate, support, attract, and retain Mission Driven Bureaucrats should have a larger place in our thinking and practice…(More)”.

Not all ‘open source’ AI models are actually open: here’s a ranking

Curated on Posted on by Stefaan Verhulst

Article by Elizabeth Gibney: “Technology giants such as Meta and Microsoft are describing their artificial intelligence (AI) models as ‘open source’ while failing to disclose important information about the underlying technology, say researchers who analysed a host of popular chatbot models.

The definition of open source when it comes to AI models is not yet agreed, but advocates say that ’full’ openness boosts science, and is crucial for efforts to make AI accountable. What counts as open source is likely to take on increased importance when the European Union’s Artificial Intelligence Act comes into force. The legislation will apply less strict regulations to models that are classed as open.

Some big firms are reaping the benefits of claiming to have open-source models, while trying “to get away with disclosing as little as possible”, says Mark Dingemanse, a language scientist at Radboud University in Nijmegen, the Netherlands. This practice is known as open-washing.

“To our surprise, it was the small players, with relatively few resources, that go the extra mile,” says Dingemanse, who together with his colleague Andreas Liesenfeld, a computational linguist, created a league table that identifies the most and least open models (see table). They published their findings on 5 June in the conference proceedings of the 2024 ACM Conference on Fairness, Accountability and Transparency…(More)”.

Governance in silico: Experimental sandbox for policymaking over AI Agents

Curated on Posted on by Stefaan Verhulst

Paper by Denisa Reshef Keraa, Eilat Navonb and Galit Well: “The concept of ‘governance in silico’ summarizes and questions the various design and policy experiments with synthetic data and content in public policy, such as synthetic data simulations, AI agents, and digital twins. While it acknowledges the risks of AI-generated hallucinations, errors, and biases, often reflected in the parameters and weights of the ML models, it focuses on the prompts. Prompts enable stakeholder negotiation and representation of diverse agendas and perspectives that support experimental and inclusive policymaking. To explore the prompts’ engagement qualities, we conducted a pilot study on co-designing AI agents for negotiating contested aspects of the EU Artificial Intelligence Act (EU AI Act). The experiments highlight the value of an ‘exploratory sandbox’ approach, which fosters political agency through direct representation over AI agent simulations. We conclude that such ‘governance in silico’ exploratory approach enhances public consultation and engagement and presents a valuable alternative to the frequently overstated promises of evidence-based policy…(More)”.

Artificial Intelligence Is Making The Housing Crisis Worse

Curated on Posted on by Stefaan Verhulst

Article by Rebecca Burns: “When Chris Robinson applied to move into a California senior living community five years ago, the property manager ran his name through an automated screening program that reportedly used artificial intelligence to detect “higher-risk renters.” Robinson, then 75, was denied after the program assigned him a low score — one that he later learned was based on a past conviction for littering.

Not only did the crime have little bearing on whether Robinson would be a good tenant, it wasn’t even one that he’d committed. The program had turned up the case of a 33-year-old man with the same name in Texas — where Robinson had never lived. He eventually corrected the error but lost the apartment and his application fee nonetheless, according to a federal class-action lawsuit that moved towards settlement this month. The credit bureau TransUnion, one of the largest actors in the multi-billion-dollar tenant screening industry, agreed to pay $11.5 million to resolve claims that its programs violated fair credit reporting laws.

Landlords are increasingly turning to private equity-backed artificial intelligence (AI) screening programs to help them select tenants, and resulting cases like Robinson’s are just the tip of the iceberg. The prevalence of incorrect, outdated, or misleading information in such reports is increasing costs and barriers to housing, according to a recent report from federal consumer regulators.

Even when screening programs turn up real data, housing and privacy advocates warn that opaque algorithms are enshrining high-tech discrimination in an already unequal housing market — the latest example of how AI can end up amplifying existing biases…(More)”.