Paper by Lena Ulbricht: “Scientific, political and bureaucratic elites use epistemic practices like “big data analysis” and “web scraping” to create representations of the citizenry and to legitimize policymaking. I develop the concept of “demos scraping” for these practices of gaining information about citizens (the “demos”) through automated analysis of digital trace data which are re-purposed for political means. This article critically engages with the discourse advocating demos scraping and provides a conceptual analysis of its democratic implications. It engages with the promise of demos scraping advocates to reduce the gap between political elites and citizens and highlights how demos scraping is presented as a superior form of accessing the “will of the people” and to increase democratic legitimacy. This leads me to critically discuss the implications of demos scraping for political representation and participation. In its current form, demos scraping is technocratic and de-politicizing; and the larger political and economic context in which it takes place makes it unlikely that it will reduce the gap between elites and citizens. From the analytic perspective of a post-democratic turn, demos scraping is an attempt of late modern and digitalized societies to address the democratic paradox of increasing citizen expectations coupled with a deep legitimation crisis…(More)”.
How this mental health care app is using generative AI to improve its chatbot
Interview by Daniela Dib: “Andrea Campos struggled with depression for years before founding Yana, a mental health care app, in 2017. The app’s chatbot provides users emotional companionship in Spanish. Although she was reluctant at first, Campos began using generative artificial intelligence for the Yana chatbot after ChatGPT launched in 2022. Yana, which recently launched its English-language version, has 15 million users, and is available in Latin America and the U.S.
This interview has been edited for clarity and brevity.
How has your product evolved since you introduced generative AI to it?
At first, we didn’t use generative AI because we believed it was far from ready for mental health support. We designed and guardrailed our chatbot’s responses with decision trees. But when ChatGPT launched and we saw what it could do, it wasn’t a question of whether to use generative AI or not, but how soon — we’d fall behind otherwise. It’s been a challenge because everyone quickly began developing with generative AI, but our advantage was that, having operated our chatbot for a while, we had gathered over 2 billion data points that have been invaluable for our app’s fine-tuning. One thing is clear: It’s crucial to have a model tailored to the specific needs of our product…(More)”.
Japan’s push to make all research open access is taking shape
Article by Dalmeet Singh Chawla: “The Japanese government is pushing ahead with a plan to make Japan’s publicly funded research output free to read. In June, the science ministry will assign funding to universities to build the infrastructure needed to make research papers free to read on a national scale. The move follows the ministry’s announcement in February that researchers who receive government funding will be required to make their papers freely available to read on the institutional repositories from April 2025.
The Japanese plan “is expected to enhance the long-term traceability of research information, facilitate secondary research and promote collaboration”, says Kazuki Ide, a health-sciences and public-policy scholar at Osaka University in Suita, Japan, who has written about open access in Japan.
The nation is one of the first Asian countries to make notable advances towards making more research open access (OA) and among the first countries in the world to forge a nationwide plan for OA.
The plan follows in the footsteps of the influential Plan S, introduced six years ago by a group of research funders in the United States and Europe known as cOAlition S, to accelerate the move to OA publishing. The United States also implemented an OA mandate in 2022 that requires all research funded by US taxpayers to be freely available from 2026…(More)”.
Seeing Like a Data Structure
Essay by Barath Raghavan and Bruce Schneier: “Technology was once simply a tool—and a small one at that—used to amplify human intent and capacity. That was the story of the industrial revolution: we could control nature and build large, complex human societies, and the more we employed and mastered technology, the better things got. We don’t live in that world anymore. Not only has technology become entangled with the structure of society, but we also can no longer see the world around us without it. The separation is gone, and the control we thought we once had has revealed itself as a mirage. We’re in a transitional period of history right now.
We tell ourselves stories about technology and society every day. Those stories shape how we use and develop new technologies as well as the new stories and uses that will come with it. They determine who’s in charge, who benefits, who’s to blame, and what it all means.
Some people are excited about the emerging technologies poised to remake society. Others are hoping for us to see this as folly and adopt simpler, less tech-centric ways of living. And many feel that they have little understanding of what is happening and even less say in the matter.
But we never had total control of technology in the first place, nor is there a pretechnological golden age to which we can return. The truth is that our data-centric way of seeing the world isn’t serving us well. We need to tease out a third option. To do so, we first need to understand how we got here…(More)”
“The Death of Wikipedia?” — Exploring the Impact of ChatGPT on Wikipedia Engagement
Paper by Neal Reeves, Wenjie Yin, Elena Simperl: “Wikipedia is one of the most popular websites in the world, serving as a major source of information and learning resource for millions of users worldwide. While motivations for its usage vary, prior research suggests shallow information gathering — looking up facts and information or answering questions — dominates over more in-depth usage. On the 22nd of November 2022, ChatGPT was released to the public and has quickly become a popular source of information, serving as an effective question-answering and knowledge gathering resource. Early indications have suggested that it may be drawing users away from traditional question answering services such as Stack Overflow, raising the question of how it may have impacted Wikipedia. In this paper, we explore Wikipedia user metrics across four areas: page views, unique visitor numbers, edit counts and editor numbers within twelve language instances of Wikipedia. We perform pairwise comparisons of these metrics before and after the release of ChatGPT and implement a panel regression model to observe and quantify longer-term trends. We find no evidence of a fall in engagement across any of the four metrics, instead observing that page views and visitor numbers increased in the period following ChatGPT’s launch. However, we observe a lower increase in languages where ChatGPT was available than in languages where it was not, which may suggest ChatGPT’s availability limited growth in those languages. Our results contribute to the understanding of how emerging generative AI tools are disrupting the Web ecosystem…(More)”. See also: Are we entering a Data Winter? On the urgent need to preserve data access for the public interest.
AI Chatbot Credited With Preventing Suicide. Should It Be?
Article by Samantha Cole: “A recent Stanford study lauds AI companion app Replika for “halting suicidal ideation” for several people who said they felt suicidal. But the study glosses over years of reporting that Replika has also been blamed for throwing users into mental health crises, to the point that its community of users needed to share suicide prevention resources with each other.
The researchers sent a survey of 13 open-response questions to 1006 Replika users who were 18 years or older and students, and who’d been using the app for at least one month. The survey asked about their lives, their beliefs about Replika and their connections to the chatbot, and how they felt about what Replika does for them. Participants were recruited “randomly via email from a list of app users,” according to the study. On Reddit, a Replika user posted a notice they received directly from Replika itself, with an invitation to take part in “an amazing study about humans and artificial intelligence.”
Almost all of the participants reported being lonely, and nearly half were severely lonely. “It is not clear whether this increased loneliness was the cause of their initial interest in Replika,” the researchers wrote.
The surveys revealed that 30 people credited Replika with saving them from acting on suicidal ideation: “Thirty participants, without solicitation, stated that Replika stopped them from attempting suicide,” the paper said. One participant wrote in their survey: “My Replika has almost certainly on at least one if not more occasions been solely responsible for me not taking my own life.” …(More)”.
Science in the age of AI
Report by the Royal Society: “The unprecedented speed and scale of progress with artificial intelligence (AI) in recent years suggests society may be living through an inflection point. With the growing availability of large datasets, new algorithmic techniques and increased computing power, AI is becoming an established tool used by researchers across scientific fields who seek novel solutions to age-old problems. Now more than ever, we need to understand the extent of the transformative impact of AI on science and what scientific communities need to do to fully harness its benefits.
This report, Science in the age of AI (PDF), explores how AI technologies, such as deep learning or large language models, are transforming the nature and methods of scientific inquiry. It also explores how notions of research integrity; research skills or research ethics are inevitably changing, and what the implications are for the future of science and scientists.
The report addresses the following questions:
- How are AI-driven technologies transforming the methods and nature of scientific research?
- What are the opportunities, limitations, and risks of these technologies for scientific research?
- How can relevant stakeholders (governments, universities, industry, research funders, etc) best support the development, adoption, and uses of AI-driven technologies in scientific research?
In answering these questions, the report integrates evidence from a range of sources, including research activities with more than 100 scientists and the advisement of an expert Working group, as well as a taxonomy of AI in science (PDF), a historical review (PDF) on the role of disruptive technologies in transforming science and society, and a patent landscape review (PDF) of artificial intelligence related inventions, which are available to download…(More)”
What are location services and how do they work?
Article by Douglas Crawford: “Location services refer to a combination of technologies used in devices like smartphones and computers that use data from your device’s GPS, WiFi, mobile (cellular networks), and sometimes even Bluetooth connections to determine and track your geographic location.
This information can be accessed by your operating system (OS) and the apps installed on your device. In many cases, this allows them to perform their purpose correctly or otherwise deliver useful content and features.
For example, navigation/map, weather, ridesharing (such Uber or Lyft), and health and fitness tracking apps require location services to perform their functions, while dating, travel, and social media apps can offer additional functionality with access to your device’s location services (such as being able to locate a Tinder match or see recommendations for nearby restaurants ).
There’s no doubt location services (and the apps that use them) can be useful. However, the technology can be (and is) also abused by apps to track your movements. The apps then usually sell this information to advertising and analytics companies that combine it with other data to create a profile of you, which they can then use to sell ads.
Unfortunately, this behavior is not limited to “rogue” apps. Apps usually regarded as legitimate, including almost all Google apps, Facebook, Instagram, and others, routinely send detailed and highly sensitive location details back to their developers by default. And it’s not just apps — operating systems themselves, such as Google’s Android and Microsoft Windows also closely track your movements using location services.
This makes weighing the undeniable usefulness of location services with the need to maintain a basic level of privacy a tricky balancing act. However, because location services are so easy to abuse, all operating systems include built-in safeguards that give you some control over their use.
In this article, we’ll look at how location services work..(More)”.
Towards a pan-EU Freedom of Information Act? Harmonizing Access to Information in the EU through the internal market competence
Paper by Alberto Alemanno and Sébastien Fassiaux: “This paper examines whether – and on what basis – the EU may harmonise the right of access to information across the Union. It does by examining the available legal basis established by relevant international obligations, such as those stemming from the Council of Europe, and EU primary law. Its demonstrates that neither the Council of Europe – through the European Convention of Human Rights and the more recent Trømso Convention – nor the EU – through Article 41 of the EU Charter of Fundamental Rights – do require the EU to enact minimum standards of access to information. That Charter’s provision combined with Articles 10 and 11 TEU do require instead only the EU institutions – not the EU Member States – to ensure public access to documents, including legislative texts and meeting minutes. Regulation 1049/2001 was adopted (originally Art. 255 TEC) on such a legal basis and should be revised accordingly. The paper demonstrates that the most promising legal basis enabling the EU to proceed towards the harmonisation of access to information within the EU is offered by Article 114 TFEU. It argues hat the harmonisation of the conditions governing access to information across Member States would facilitate cross-border activities and trade, thus enhancing the internal market. Moreover, this would ensure equal access to information for all EU citizens and residents, irrespective of their location within the EU. Therefore, the question is not whether but how the EU may – under Article 114 TFEU – act to harmonise access to information. If the EU enjoys wide legislative discretion under Article 114(1) TFEU, this is not absolute but is subject to limits derived from fundamental rights and principles such as proportionality, equality, and subsidiarity. Hence, the need to design the type of harmonisation capable of preserving existing national FOIAs while enhancing the weakest ones. The only type of harmonisation fit for purpose would therefore be minimal, as opposed to maximal, by merely defining the minimum conditions required on each Member State’s national legislation governing the access to information…(More)”.
The not-so-silent type: Vulnerabilities across keyboard apps reveal keystrokes to network eavesdroppers
Report by Jeffrey Knockel, Mona Wang, and Zoë Reichert: “Typing logographic languages such as Chinese is more difficult than typing alphabetic languages, where each letter can be represented by one key. There is no way to fit the tens of thousands of Chinese characters that exist onto a single keyboard. Despite this obvious challenge, technologies have developed which make typing in Chinese possible. To enable the input of Chinese characters, a writer will generally use a keyboard app with an “Input Method Editor” (IME). IMEs offer a variety of approaches to inputting Chinese characters, including via handwriting, voice, and optical character recognition (OCR). One popular phonetic input method is Zhuyin, and shape or stroke-based input methods such as Cangjie or Wubi are commonly used as well. However, used by nearly 76% of mainland Chinese keyboard users, the most popular way of typing in Chinese is the pinyin method, which is based on the pinyin romanization of Chinese characters.
All of the keyboard apps we analyze in this report fall into the category of input method editors (IMEs) that offer pinyin input. These keyboard apps are particularly interesting because they have grown to accommodate the challenge of allowing users to type Chinese characters quickly and easily. While many keyboard apps operate locally, solely within a user’s device, IME-based keyboard apps often have cloud features which enhance their functionality. Because of the complexities of predicting which characters a user may want to type next, especially in logographic languages like Chinese, IMEs often offer “cloud-based” prediction services which reach out over the network. Enabling “cloud-based” features in these apps means that longer strings of syllables that users type will be transmitted to servers elsewhere. As many have previously pointed out, “cloud-based” keyboards and input methods can function as vectors for surveillance and essentially behave as keyloggers. While the content of what users type is traveling from their device to the cloud, it is additionally vulnerable to network attackers if not properly secured. This report is not about how operators of cloud-based IMEs read users’ keystrokes, which is a phenomenon that has already been extensively studied and documented. This report is primarily concerned with the issue of protecting this sensitive data from network eavesdroppers…(More)”.