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
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
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
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
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
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
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
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)”.
What the Arrival of A.I. Phones and Computers Means for Our Data
Article by Brian X. Chen: “Apple, Microsoft and Google are heralding a new era of what they describe as artificially intelligent smartphones and computers. The devices, they say, will automate tasks like editing photos and wishing a friend a happy birthday.
But to make that work, these companies need something from you: more data.
In this new paradigm, your Windows computer will take a screenshot of everything you do every few seconds. An iPhone will stitch together information across many apps you use. And an Android phone can listen to a call in real time to alert you to a scam.
Is this information you are willing to share?
This change has significant implications for our privacy. To provide the new bespoke services, the companies and their devices need more persistent, intimate access to our data than before. In the past, the way we used apps and pulled up files and photos on phones and computers was relatively siloed. A.I. needs an overview to connect the dots between what we do across apps, websites and communications, security experts say.
“Do I feel safe giving this information to this company?” Cliff Steinhauer, a director at the National Cybersecurity Alliance, a nonprofit focusing on cybersecurity, said about the companies’ A.I. strategies.
All of this is happening because OpenAI’s ChatGPT upended the tech industry nearly two years ago. Apple, Google, Microsoft and others have since overhauled their product strategies, investing billions in new services under the umbrella term of A.I. They are convinced this new type of computing interface — one that is constantly studying what you are doing to offer assistance — will become indispensable.
The biggest potential security risk with this change stems from a subtle shift happening in the way our new devices work, experts say. Because A.I. can automate complex actions — like scrubbing unwanted objects from a photo — it sometimes requires more computational power than our phones can handle. That means more of our personal data may have to leave our phones to be dealt with elsewhere.
The information is being transmitted to the so-called cloud, a network of servers that are processing the requests. Once information reaches the cloud, it could be seen by others, including company employees, bad actors and government agencies. And while some of our data has always been stored in the cloud, our most deeply personal, intimate data that was once for our eyes only — photos, messages and emails — now may be connected and analyzed by a company on its servers…(More)”.
Connecting the dots: AI is eating the web that enabled it
Article by Tom Wheeler: “The large language models (LLMs) of generative AI that scraped their training data from websites are now using that data to eliminate the need to go to many of those same websites. Respected digital commentator Casey Newton concluded, “the web is entering a state of managed decline.” The Washington Post headline was more dire: “Web publishers brace for carnage as Google adds AI answers.”…
Created by Sir Tim Berners-Lee in 1989, the World Wide Web redefined the nature of the internet into a user-friendly linkage of diverse information repositories. “The first decade of the web…was decentralized with a long-tail of content and options,” Berners-Lee wrote this year on the occasion of its 35th anniversary. Over the intervening decades, that vision of distributed sources of information has faced multiple challenges. The dilution of decentralization began with powerful centralized hubs such as Facebook and Google that directed user traffic. Now comes the ultimate disintegration of Berners-Lee’s vision as generative AI reduces traffic to websites by recasting their information.
The web’s open access to the world’s information trained the large language models (LLMs) of generative AI. Now, those generative AI models are coming for their progenitor.
The web allowed users to discover diverse sources of information from which to draw conclusions. AI cuts out the intellectual middleman to go directly to conclusions from a centralized source.
The AI paradigm of cutting out the middleman appears to have been further advanced in Apple’s recent announcement that it will incorporate OpenAI to enable its Siri app to provide ChatGPT-like answers. With this new deal, Apple becomes an AI-based disintermediator, not only eliminating the need to go to websites, but also potentially disintermediating the need for the Google search engine for which Apple has been paying $20 billion annually.
The Atlantic, University of Toronto, and Gartner studies suggest the Pew research on website mortality could be just the beginning. Generative AI’s ability to deliver conclusions cannibalizes traffic to individual websites threatening the raison d’être of all websites, especially those that are commercially supported…(More)”