The Rise of Cyber-Physical Systems


Article by Chandrakant D. Patel: “Cyber-physical systems are a systemic integration of physical and cyber technologies. To name one example, a self-driving car is an integration of physical technologies, such as motors, batteries, actuators, and sensors, and cyber technologies, like communication, computation, inference, and closed-loop control. Data flow from physical to cyber technologies results in systemic integration and the desired driving experience. Cyber-physical systems are becoming prevalent in a range of sectors, such as power, water, waste, transportation, healthcare, agriculture, and manufacturing. We have entered the cyber-physical age. However, we stand unprepared for this moment due to systemic under-allocation in the physical sciences and the lack of a truly multidisciplinary engineering curriculum.  While there are many factors that contribute to the rise of cyber-physical systems, societal challenges stemming from imbalances between supply and demand are becoming a very prominent one. These imbalances are caused by social, economic, and ecological trends that hamper the delivery of basic goods and services. Examples of trends leading to imbalances between supply and demand are resource constraints, aging population, human capital constraints, a lack of subject matter experts in critical fields, physical security risks, supply-chain and supply-side resiliency, and externalities such as pandemics and environmental pollution. With respect to the lack of subject matter experts, consider the supply of cardiothoracic surgeons. The United States has about 4000 cardiothoracic surgeons, a sub-specialization that takes 20 years of education and hands-on training, for a population of 333 million. Similar imbalances in subject matter experts in healthcare, power, water, waste, and transport systems are occurring as a result of aging population. Compounding this challenge is the market-driven pay discrepancy that has attracted our youth to software jobs, such as those in social media, which pay much more relative to the salaries for a resident in general surgery or an early-career civil engineer. While it is possible that the market will shift to value infrastructure- and healthcare-related jobs, the time it takes to train “hands-on” contributors (e.g., engineers and technicians) in physical sciences and life sciences is substantial, ranging from 5 years (technicians requiring industry training) to 20 years (sub-specialized personnel like cardiothoracic surgeons)…(More)”.

Where Did the Open Access Movement Go Wrong?


An Interview with Richard Poynder by Richard Anderson: “…Open access was intended to solve three problems that have long blighted scholarly communication – the problems of accessibilityaffordability, and equity. 20+ years after the Budapest Open Access Initiative (BOAI) we can see that the movement has signally failed to solve the latter two problems. And with the geopolitical situation deteriorating solving the accessibility problem now also looks to be at risk. The OA dream of “universal open access” remains a dream and seems likely to remain one.

What has been the essence of the OA movement’s failure?

The fundamental problem was that OA advocates did not take ownership of their own movement. They failed, for instance, to establish a central organization (an OA foundation, if you like) in order to organize and better manage the movement; and they failed to publish a single, canonical definition of open access. This is in contrast to the open source movement, and is an omission I drew attention to in 2006

This failure to take ownership saw responsibility for OA pass to organizations whose interests are not necessarily in sync with the objectives of the movement.

It did not help that the BOAI definition failed to specify that to be classified as open access, scholarly works needed to be made freely available immediately on publication and that they should remain freely available in perpetuity. Nor did it give sufficient thought to how OA would be funded (and OA advocates still fail to do that).

This allowed publishers to co-opt OA for their own purposes, most notably by introducing embargoes and developing the pay-to-publish gold OA model, with its now infamous article processing charge (APC).

Pay-to-publish OA is now the dominant form of open access and looks set to increase the cost of scholarly publishing and so worsen the affordability problem. Amongst other things, this has disenfranchised unfunded researchers and those based in the global south (notwithstanding APC waiver promises).

What also did not help is that OA advocates passed responsibility for open access over to universities and funders. This was contradictory, because OA was conceived as something that researchers would opt into. The assumption was that once the benefits of open access were explained to them, researchers would voluntarily embrace it – primarily by self-archiving their research in institutional or preprint repositories. But while many researchers were willing to sign petitions in support of open access, few (outside disciplines like physics) proved willing to practice it voluntarily.

In response to this lack of engagement, OA advocates began to petition universities, funders, and governments to introduce OA policies recommending that researchers make their papers open access. When these policies also failed to have the desired effect, OA advocates demanded their colleagues be forced to make their work OA by means of mandates requiring them to do so.

Most universities and funders (certainly in the global north) responded positively to these calls, in the belief that open access would increase the pace of scientific development and allow them to present themselves as forward-thinking, future-embracing organizations. Essentially, they saw it as a way of improving productivity and ROI while enhancing their public image.

While many researchers were willing to sign petitions in support of open access, few proved willing to practice it voluntarily.

But in light of researchers’ continued reluctance to make their works open access, universities and funders began to introduce increasingly bureaucratic rules, sanctions, and reporting tools to ensure compliance, and to manage the more complex billing arrangements that OA has introduced.

So, what had been conceived as a bottom-up movement founded on principles of voluntarism morphed into a top-down system of command and control, and open access evolved into an oppressive bureaucratic process that has failed to address either the affordability or equity problems. And as the process, and the rules around that process, have become ever more complex and oppressive, researchers have tended to become alienated from open access.

As a side benefit for universities and funders OA has allowed them to better micromanage their faculty and fundees, and to monitor their publishing activities in ways not previously possible. This has served to further proletarianize researchers and today they are becoming the academic equivalent of workers on an assembly line. Philip Mirowski has predicted that open access will lead to the deskilling of academic labor. The arrival of generative AI might seem to make that outcome the more likely…

Can these failures be remedied by means of an OA reset? With this aim in mind (and aware of the failures of the movement), OA advocates are now devoting much of their energy to trying to persuade universities, funders, and philanthropists to invest in a network of alternative nonprofit open infrastructures. They envisage these being publicly owned and focused on facilitating a flowering of new diamond OA journals, preprint servers, and Publish, Review, Curate (PRC) initiatives. In the process, they expect commercial publishers will be marginalized and eventually dislodged.

But it is highly unlikely that the large sums of money that would be needed to create these alternative infrastructures will be forthcoming, certainly not at sufficient levels or on anything other than a temporary basis.

While it is true that more papers and preprints are being published open access each year, I am not convinced this is taking us down the road to universal open access, or that there is a global commitment to open access.

Consequently, I do not believe that a meaningful reset is possible: open access has reached an impasse and there is no obvious way forward that could see the objectives of the OA movement fulfilled.

Partly for this reason, we are seeing attempts to rebrand, reinterpret, and/or reimagine open access and its objectives…(More)”.

Rebalancing AI


Article by Daron Acemoglu and Simon Johnson: “Optimistic forecasts regarding the growth implications of AI abound. AI adoption could boost productivity growth by 1.5 percentage points per year over a 10-year period and raise global GDP by 7 percent ($7 trillion in additional output), according to Goldman Sachs. Industry insiders offer even more excited estimates, including a supposed 10 percent chance of an “explosive growth” scenario, with global output rising more than 30 percent a year.

All this techno-optimism draws on the “productivity bandwagon”: a deep-rooted belief that technological change—including automation—drives higher productivity, which raises net wages and generates shared prosperity.

Such optimism is at odds with the historical record and seems particularly inappropriate for the current path of “just let AI happen,” which focuses primarily on automation (replacing people). We must recognize that there is no singular, inevitable path of development for new technology. And, assuming that the goal is to sustainably improve economic outcomes for more people, what policies would put AI development on the right path, with greater focus on enhancing what all workers can do?…(More)”

What Will AI Do to Elections?


Article by Rishi Iyengar: “…Requests to X’s press team on how the platform was preparing for elections in 2024 yielded an automated response: “Busy now, please check back later”—a slight improvement from the initial Musk-era change where the auto-reply was a poop emoji.

X isn’t the only major social media platform with fewer content moderators. Meta, which owns Facebook, Instagram, and WhatsApp, has laid off more than 20,000 employees since November 2022—several of whom worked on trust and safety—while many YouTube employees working on misinformation policy were impacted by layoffs at parent company Google.

There could scarcely be a worse time to skimp on combating harmful content online. More than 50 countries, including the world’s three biggest democracies and Taiwan, an increasingly precarious geopolitical hot spot, are expected to hold national elections in 2024. Seven of the world’s 10 most populous countries—Bangladesh, India, Indonesia, Mexico, Pakistan, Russia, and the United States—will collectively send a third of the world’s population to the polls.

Elections, with their emotionally charged and often tribal dynamics, are where misinformation missteps come home to roost. If social media misinformation is the equivalent of yelling “fire” in a crowded theater, election misinformation is like doing so when there’s a horror movie playing and everyone’s already on edge.

Katie Harbath prefers a different analogy, one that illustrates how nebulous and thorny the issues are and the sheer uncertainty surrounding them. “The metaphor I keep using is a kaleidoscope because there’s so many different aspects to this but depending how you turn the kaleidoscope, the pattern changes of what it’s going to look like,” she said in an interview in October. “And that’s how I feel about life post-2024. … I don’t know where in the kaleidoscope it’s going to land.”

Harbath has become something of an election whisperer to the tech industry, having spent a decade at Facebook from 2011 building the company’s election integrity efforts from scratch. She left in 2021 and founded Anchor Change, a public policy consulting firm that helps other platforms combat misinformation and prepare for elections in particular.

Had she been in her old job, Harbath said, her team would have completed risk assessments of global elections by late 2022 or early 2023 and then spent the rest of the year tailoring Meta’s products to them as well as setting up election “war rooms” where necessary. “Right now, we would be starting to move into execution mode.” She cautions against treating the resources that companies are putting into election integrity as a numbers game—“once you build some of those tools, maintaining them doesn’t take as many people”—but acknowledges that the allocation of resources reveals a company leadership’s priorities.

The companies insist they remain committed to election integrity. YouTube has “heavily invested in the policies and systems that help us successfully support elections around the world,” spokesperson Ivy Choi said in a statement. TikTok said it has a total of 40,000 safety professionals and works with 16 fact-checking organizations across 50 global languages. Meta declined to comment for this story, but a company representative directed Foreign Policy to a recent blog post by Nick Clegg, a former U.K. deputy prime minister who now serves as Meta’s head of global affairs. “We have around 40,000 people working on safety and security, with more than $20 billion invested in teams and technology in this area since 2016,” Clegg wrote in the post.

But there are other troubling signs. YouTube announced last June that it would stop taking down content spreading false claims about the 2020 U.S. election or past elections, and Meta quietly made a similar policy change to its political ad rules in 2022. And as past precedent has shown, the platforms tend to have even less cover outside the West, with major blind spots in local languages and context making misinformation and hate speech not only more pervasive but also more dangerous…(More)”.

Forget technology — politicians pose the gravest misinformation threat


Article by Rasmus Nielsen: “This is set to be a big election year, including in India, Mexico, the US, and probably the UK. People will rightly be on their guard for misinformation, but much of the policy discussion on the topic ignores the most important source: members of the political elite.

As a social scientist working on political communication, I have spent years in these debates — which continue to be remarkably disconnected from what we know from research. Academic findings repeatedly underline the actual impact of politics, while policy documents focus persistently on the possible impact of new technologies.

Most recently, Britain’s National Cyber Security Centre (NCSC) has warned of how “AI-created hyper-realistic bots will make the spread of disinformation easier and the manipulation of media for use in deepfake campaigns will likely become more advanced”. This is similar to warnings from many other public authorities, which ignore the misinformation from the most senior levels of domestic politics. In the US, the Washington Post stopped counting after documenting at least 30,573 false or misleading claims made by Donald Trump as president. In the UK, the non-profit FullFact has reported that as many as 50 MPs — including two prime ministers, cabinet ministers and shadow cabinet ministers — failed to correct false, unevidenced or misleading claims in 2022 alone, despite repeated calls to do so.

These are actual problems of misinformation, and the phenomenon is not new. Both George W Bush and Barack Obama’s administrations obfuscated on Afghanistan. Bush’s government and that of his UK counterpart Tony Blair advanced false and misleading claims in the run-up to the Iraq war. Prominent politicians have, over the years, denied the reality of human-induced climate change, proposed quack remedies for Covid-19, and so much more. These are examples of misinformation, and, at their most egregious, of disinformation — defined as spreading false or misleading information for political advantage or profit.

This basic point is strikingly absent from many policy documents — the NCSC report, for example, has nothing to say about domestic politics. It is not alone. Take the US Surgeon General’s 2021 advisory on confronting health misinformation which calls for a “whole-of-society” approach — and yet contains nothing on politicians and curiously omits the many misleading claims made by the sitting president during the pandemic, including touting hydroxychloroquine as a potential treatment…(More)”.

The 2010 Census Confidentiality Protections Failed, Here’s How and Why


Paper by John M. Abowd, et al: “Using only 34 published tables, we reconstruct five variables (census block, sex, age, race, and ethnicity) in the confidential 2010 Census person records. Using the 38-bin age variable tabulated at the census block level, at most 20.1% of reconstructed records can differ from their confidential source on even a single value for these five variables. Using only published data, an attacker can verify that all records in 70% of all census blocks (97 million people) are perfectly reconstructed. The tabular publications in Summary File 1 thus have prohibited disclosure risk similar to the unreleased confidential microdata. Reidentification studies confirm that an attacker can, within blocks with perfect reconstruction accuracy, correctly infer the actual census response on race and ethnicity for 3.4 million vulnerable population uniques (persons with nonmodal characteristics) with 95% accuracy, the same precision as the confidential data achieve and far greater than statistical baselines. The flaw in the 2010 Census framework was the assumption that aggregation prevented accurate microdata reconstruction, justifying weaker disclosure limitation methods than were applied to 2010 Census public microdata. The framework used for 2020 Census publications defends against attacks that are based on reconstruction, as we also demonstrate here. Finally, we show that alternatives to the 2020 Census Disclosure Avoidance System with similar accuracy (enhanced swapping) also fail to protect confidentiality, and those that partially defend against reconstruction attacks (incomplete suppression implementations) destroy the primary statutory use case: data for redistricting all legislatures in the country in compliance with the 1965 Voting Rights Act…(More)”.

Eat, Click, Judge: The Rise of Cyber Jurors on China’s Food Apps


Article from Ye Zhanhang: “From unwanted ingredients in takeaway meals and negative restaurant reviews to late deliveries and poor product quality, digital marketplaces teem with minor frustrations. 

But because they affect customer satisfaction and business reputations, several Chinese online shopping platforms have come up with a unique solution: Ordinary users can become “cyber jurors” to deliberate and cast decisive votes in resolving disputes between buyers and sellers.

Though introduced in 2020, the concept has surged in popularity among young Chinese in recent months, primarily fueled by viral cases that users eagerly follow, scrutinizing every detail and deliberation online…

To be eligible for the role, a user must meet certain criteria, including having a verified account, maintaining consumption records within the past three months, and successfully navigating five mock cases as part of an entry test. Cyber jurors don’t receive any money for completing cases but may be rewarded with coupons.

Xianyu, an online secondhand shopping platform, has also introduced a “court” system that assembles a jury of 17 volunteer users to adjudicate disputes between buyers and sellers. 

Miao Mingyu, a law professor at the University of Chinese Academy of Social Sciences, told China Youth Daily that this public jury function, with its impartial third-party perspective, has the potential to enhance transaction transparency and the fairness of the platform’s evaluation system.

Despite Chinese law prohibiting platforms from removing user reviews of products, Miao noted that this feature has enabled the platform to effectively address unfair negative reviews without violating legal constraints…(More)”.

Introduction to Digital Humanism


Open access textbook edited by Hannes Werthner et al: “…introduces and defines digital humanism from a diverse range of disciplines. Following the 2019 Vienna Manifesto, the book calls for a digital humanism that describes, analyzes, and, most importantly, influences the complex interplay of technology and humankind, for a better society and life, fully respecting universal human rights.The book is organized in three parts: Part I “Background” provides the multidisciplinary background needed to understand digital humanism in its philosophical, cultural, technological, historical, social, and economic dimensions. The goal is to present the necessary knowledge upon which an effective interdisciplinary discourse on digital humanism can be founded. Part II “Digital Humanism – a System’s View” focuses on an in-depth presentation and discussion of the main digital humanism concerns arising in current digital systems. The goal of this part is to make readers aware and sensitive to these issues, including e.g. the control and autonomy of AI systems, privacy and security, and the role of governance. Part III “Critical and Societal Issues of Digital Systems” delves into critical societal issues raised by advances of digital technologies. While the public debate in the past has often focused on them separately, especially when they became visible through sensational events the aim here is to shed light on the entire landscape and show their interconnected relationships. This includes issues such as AI and ethics, fairness and bias, privacy and surveillance, platform power and democracy.

This textbook is intended for students, teachers, and policy makers interested in digital humanism. It is designed for stand-alone and for complementary courses in computer science, or curricula in science, engineering, humanities and social sciences. Each chapter includes questions for students and an annotated reading list to dive deeper into the associated chapter material. The book aims to provide readers with as wide an exposure as possible to digital advances and their consequences for humanity. It includes constructive ideas and approaches that seek to ensure that our collective digital future is determined through human agency…(More)”.

How can Mixed Reality and AI improve emergency medical care?


Springwise: “Mixed reality (MR) refers to technologies that create immersive computer-generated environments in which parts of the physical and virtual environment are combined. With potential applications that range from education and engineering to entertainment, the market for MR is forecast to record revenues of just under $25 billion by 2032. Now, in a ground-breaking partnership, Singapore-based company Mediwave is teaming up with Sri Lanka’s 1990 Suwa Seriya to deploy MR and artificial intelligence (AI) to create a fully connected ambulance.

1990 Suwa Seriya is Sri Lanka’s national pre-hospital emergency ambulance service, which boasts response times that surpass even some services in developed countries. The innovative ambulance it has deployed uses Mediwave’s integrated Emergency Response Suite, which combines the latest communications equipment with internet-of-things (IoT) and AR capabilities to enhance the efficiency of the emergency response eco-system.

The connected ambulance ensures swift response times and digitises critical processes, while specialised care can be provided remotely through a Microsoft HoloLens. The technology enables Emergency Medical Technicians (EMTs) – staff who man ambulances in Sri Lanka – to connect with physicians at the Emergency Command and Control Centre. These physicians help the EMTs provide care during the so-called ‘golden hour’ of medical emergencies – the concept that rapid clinical investigation and care within 60 minutes of a traumatic injury is essential for a positive patient outcome…

Other applications of extended reality in the Springwise library include holograms that are used to train doctorsvirtual environments for treating phobias, and an augmented reality contact lens…(More)”.

Technology, Data and Elections: An Updated Checklist on the Election Cycle


Checklist by Privacy International: “In the last few years, electoral processes and related activities have undergone significant changes, driven by the development of digital technologies.

The use of personal data has redefined political campaigning and enabled the proliferation of political advertising tailor-made for audiences sharing specific characteristics or personalised to the individual. These new practices, combined with the platforms that enable them, create an environment that facilitate the manipulation of opinion and, in some cases, the exclusion of voters.

In parallel, governments are continuing to invest in modern infrastructure that is inherently data-intensive. Several states are turning to biometric voter registration and verification technologies ostensibly to curtail fraud and vote manipulation. This modernisation often results in the development of nationwide databases containing masses of personal, sensitive information, that require heightened safeguards and protection.

The number and nature of actors involved in the election process is also changing, and so are the relationships between electoral stakeholders. The introduction of new technologies, for example for purposes of voter registration and verification, often goes hand-in-hand with the involvement of private companies, a costly investment that is not without risk and requires robust safeguards to avoid abuse.

This new electoral landscape comes with many challenges that must be addressed in order to protect free and fair elections: a fact that is increasingly recognised by policymakers and regulatory bodies…(More)”.