The United States' competition watchdog has opened an investigation into ChatGPT creator OpenAI amid suspicions the startup broke the law by scraping public data and publishing false and defamatory information. In a 20-page letter, the US Federal Trade Commission (FTC) has requested OpenAI to provide detailed information about its technology and privacy protections, including any efforts to prevent a repeat of incidents in which its groundbreaking chatbot published false and disparaging information about members of the public. The Washington Post first reported on the "expansive" probe on Thursday. The FTC declined to comment when contacted by Al Jazeera. OpenAI chief executive Sam Altman said the leak of the regulator's probe was "disappointing" and would not help build trust.

Recently, the AI/ML research community has indicated an urgent need to establish Responsible AI (RAI) values and practices as part of the AI/ML lifecycle. Several organizations and communities are responding to this call by sharing RAI guidelines. However, there are gaps in awareness, deliberation, and execution of such practices for multi-disciplinary ML practitioners. This work contributes to the discussion by unpacking co-production challenges faced by practitioners as they align their RAI values. We interviewed 23 individuals, across 10 organizations, tasked to ship AI/ML based products while upholding RAI norms and found that both top-down and bottom-up institutional structures create burden for different roles preventing them from upholding RAI values, a challenge that is further exacerbated when executing conflicted values. We share multiple value levers used as strategies by the practitioners to resolve their challenges. We end our paper with recommendations for inclusive and equitable RAI value-practices, creating supportive organizational structures and opportunities to further aid practitioners.

In this paper, we propose a robustness benchmark for image-text matching models to assess their vulnerabilities. To this end, we insert adversarial texts and images into the search pool (i.e., gallery set) and evaluate models with the adversarial data. Specifically, we replace a word in the text to change the meaning of the text and mix images with different images to create perceptible changes in pixels. We assume that such explicit alterations would not deceive a robust model, as they should understand the holistic meaning of texts and images simultaneously. However, in our evaluations on the proposed benchmark, many state-of-the-art models show significant performance degradation, e.g., Recall@1: 81.9% $\rightarrow$ 64.5% in BLIP, 66.1% $\rightarrow$ 37.5% in VSE$\infty$, where the models favor adversarial texts/images over the original ones. This reveals the current vision-language models may not account for subtle changes or understand the overall context of texts and images. Our findings can provide insights for improving the robustness of the vision-language models and devising more diverse stress-test methods in cross-modal retrieval task. Source code and dataset will be available at https://github.com/pseulki/rococo.

The problem of change detection in images finds application in different domains like diagnosis of diseases in the medical field, detecting growth patterns of cities through remote sensing, and finding changes in legal documents and contracts. However, this paper presents a survey on core techniques and rules to detect changes in different versions of a document image. Our discussions on change detection focus on two categories -- content-based and layout-based. The content-based techniques intelligently extract and analyze the image contents (text or non-text) to show the possible differences, whereas the layout-based techniques use structural information to predict document changes. We also summarize the existing datasets and evaluation metrics used in change detection experiments. The shortcomings and challenges the existing methods face are reported, along with some pointers for future research work.

Lina Khan, the chair of the Federal Trade Commission, faced a grueling four hours of questioning during a House judiciary committee oversight hearing on Thursday. Republicans criticized Khan – an outspoken critic of big tech – for "mismanagement" and for "politicizing" legal action against large companies such as Twitter and Google as head of the powerful antitrust agency. In his opening statement, committee chair Jim Jordan, an Ohio Republican, said Khan has given herself and the FTC "unchecked power" by taking aggressive steps to regulate practices at big tech companies such as Twitter, Meta and Google. He said Khan carried out "targeted harassment against Twitter" by asking for all communications related to Elon Musk, including conversations with journalists, following Musk's acquisition because she does not share his political views. Khan, a former journalist, said the company has "a history of lax security and privacy policies" that did not begin with Musk.

Now, a rising group of authors, musicians, news organizations and social media companies has been pushing back, arguing that the use of their content to train AI is a massive shift in the way the internet works, especially since some of the AI tools being trained on human-made content are already being used to replace human workers. A wave of lawsuits has washed over the industry in the past two weeks alleging improper data use, including class-action suits against OpenAI and Google, and lawsuits against OpenAI from the comedian Sarah Silverman and two prominent fiction authors.

The US Federal Trade Commission has reportedly launched an investigation into whether OpenAI, the company behind popular AI chatbot ChatGPT, has violated consumer protection laws. The FTC sent OpenAI a 20-page request for documents covering concerns related to data privacy and reputational harm, according to a report Thursday from The Washington Post. The agency also asked for details on OpenAI's large language model, the technology behind its generative AI chatbot, including all sources used to train the model and how data was obtained, according to the request, which was shared by the Post. CNET hasn't independently verified the request. The FTC declined to comment.

American regulators now appear to be clamping down on generative AI in earnest. The Washington Post has learned the Federal Trade Commission (FTC) has launched an investigation into OpenAI, the creator of ChatGPT and DALL-E. Officials have requested documents showing how the company tackles risks stemming from its large language AI models. The FTC is concerned the company may be violating consumer protection laws through "unfair or deceptive" practices that could hurt the public's privacy, security or reputation. The Commission is particularly interested in information linked to a bug that leaked ChatGPT users' sensitive data, including payments and chat histories.

São Paulo, Brazil – As the city of São Paulo prepares to roll out thousands of surveillance cameras with facial recognition, experts are raising concerns on the indiscriminate use of this technology in the Brazilian megalopolis could exacerbate problems such as structural racism and inequality, while also posing risks to data privacy and cybersecurity. The Smart Sampa project is the latest among a series of initiatives involving modern surveillance techniques in various Brazilian states. It is significant due to the sheer size of the population it will impact: São Paulo, the most populous city in the Southern Hemisphere, is home to 12 million people. The project aims to roll out a single video surveillance platform that integrates and supports the operations of emergency and traffic services, the city's public transport network, and police forces. By 2024, up to 20,000 cameras will be installed, and an equal number of third-party and private cameras will be integrated into the network.

The US's top competition watchdog has opened an investigation into OpenAI, the maker of ChatGPT, on claims it has run afoul of consumer protection laws by putting personal reputations and data at risk. The move marks the strongest regulatory threat to the Microsoft-backed startup that kicked off the frenzy in generative artificial intelligence, enthralling consumers and businesses while raising concerns about its potential risks. The Federal Trade Commission (FTC) this week sent a 20-page demand for records about how OpenAI addresses risks related to its AI models. The agency is investigating whether the company engaged in unfair or deceptive practices that resulted in "reputational harm" to consumers. One of the questions has to do with steps OpenAI has taken to address the potential for its products to "generate statements about real individuals that are false, misleading, or disparaging".