ICO warns of fines for companies who do not get cookie banners right
en-GBStephen Bonner announced that the (ICO) is "paying attention" to how companies use cookies on websites and how they allow users to configure their settings
MEPs ready to negotiate first-ever rules for safe and transparent AI | News | European Parliament
The rules aim to promote the uptake of human-centric and trustworthy AI and protect the health, safety, fundamental rights and democracy from its harmful effects.
Beth Kanter on LinkedIn: Virginia Dignum – Responsible artificial intelligence
Virginia Dignum is a professor and member of the EU’s High-Level Expert Group on AI who has been looking into the many questions that come up across society…
Let Me Take Over: Variable Autonomy for Meaningful Human Control
As Artificial Intelligence (AI) continues to expand its reach, the demand for human control and the development of AI systems that adhere to our legal, ethical, and social values also grows. Many (international and national) institutions have taken steps in this direction and published guidelines for the development and deployment of responsible AI systems. These guidelines, however, rely heavily on high-level statements that provide no clear criteria for system assessment, making the effective control over systems a challenge. “Human oversight” is one of the requirements being put forward as a means to support human autonomy and agency. In this paper, we argue that human presence alone does not meet this requirement and that such a misconception may limit the use of automation where it can otherwise provide so much benefit across industries. We therefore propose the development of systems with variable autonomy—dynamically adjustable levels of autonomy—as a means of ensuring meaningful human control over an artefact by satisfying all three core values commonly advocated in ethical guidelines: accountability, responsibility, and transparency.
ACROCPoLis: A Descriptive Framework for Making Sense of Fairness | Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency
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'Thirsty' AI: Training ChatGPT Required Enough Water to Fill a Nuclear Reactor's Cooling Tower, Study Finds
Popular large language models (LLMs) like OpenAI’s ChatGPT and Google’s Bard are energy-intensive, requiring massive server farms to provide enough data to train the powerful programs. Cooling those same data centers also makes the AI chatbots incredibly thirsty. New research suggests training for GPT-3 alone consumed 185,000 gallons (700,000 liters) of water. An average user’s conversational exchange with ChatGPT basically amounts to dumping a large bottle of fresh water out on the ground, acco
Tech Elite's AI Ideologies Have Racist Foundations, Say AI Ethicists
More and more prominent tech figures are voicing concerns about superintelligent AI and risks to the future of humanity. But as leading AI ethicist Timnit Gebru and researcher Émile P Torres point out, these ideologies have deeply racist foundations. TESCREAL “So another “godfather” of AI, Turing Award Winner Yoshua Bengio has decided to FULLY align […]
OpenAI's Altman and other AI giants back warning of advanced AI as 'extinction' risk
Hundreds of AI scientists, academics, tech CEOs and public figures have added their names to a statement urging global attention on existential AI risk.
Black men were likely underdiagnosed with lung problems because of bias in software, study suggests
A new study suggests racial bias built into a common medical test for lung function is likely leading to fewer Black patients getting care for breathing problems. The study released Thursday in JAMA Network Open found that as many as 40% more Black men might be diagnosed with breathing problems if current diagnosis-assisting computer software was changed.
How I became myself after merging with a computer: Does human-machine symbiosis raise human rights issues?
Novel usages of brain stimulation combined with artificially intelligent (AI) systems
promise to address a large range of diseases. These new conjoined technologies, such
as brain-computer interfaces (BCI), are increasingly used in experimental and clinical
settings to predict and alleviate symptoms of various neurological and psychiatric
disorders. Due to their reliance on AI algorithms for feature extraction and classification,
these BCI systems enable a novel, unprecedented, and direct connection between human
cognition and artificial information processing.