How worried are top AI experts about the threat posed by large language models like GPT-4?

As (Gen)AI's real-world utility abounds, AI is becoming a dirty word

ChatGPT may have consumed as much electricity as 175,000 people in January 2023.

As the excitement grows around machine learning and things called “AI,” it’s only natural that we would see companies, products, and…

In public, OpenAI is calling for stronger AI guardrails. But documents show the company lobbied to weaken EU regulation

Self-service technologies — like self-checkouts or government service kiosks — are decreasing interactions with other people. This may affect our politics and sense of community.

AR designers and creators are today’s magicians. Here’s what they need to know to re-enchant the world

What follows is a critical analysis of “Exploring the MIT Mathematics and EECS Curriculum Using Large Language Models”

As a generative AI training model is exposed to more AI-generated data, it performs worse, producing more errors, leading to model collapse.

The Taliban administration is stuck in a cat-and-mouse game with WhatsApp, which is off-limits to the nascent government because of U.S. sanctions.

Lawmakers are flocking to private meetings, dinners and briefings with AI experts — including the CEOs of the companies they’re trying to regulate.

Generative artificial-intelligence chatbots like ChatGPT are known to get things wrong sometimes, a process known as “hallucinating.” But can anyone be held liable if those incorrect responses are damaging in some way? Host Zoe Thomas talks to a legal expert and an AI ethicist to explore the legal landscape for generative AI technology, and the tactics companies are employing to improve their products. This is the fourth episode of Tech News Briefing’s special series on generative AI, “Artificially Minded.” 0:00 Why Australian mayor Brian Hood is thinking about suing OpenAI's ChatGPT for defamation 4:44 Why generative AI programs like OpenAI’s ChatGPT can get facts wrong 6:26 What the 1996 Communication Decency Act could tell us about laws around generative AI 10:20 How generative AI blurs the line between creator and platform 12:56 How lawmakers around the world are handing regulation around AI 14:13 Why AI hallucinations happen 17:16 How Google is taking steps to create a more factual chatbot with Bard 18:34 How tech companies work with AI ethicists: what is red teaming? Tech News Briefing WSJ’s tech podcast featuring breaking news, scoops and tips on tech innovations and policy debates, plus exclusive interviews with movers and shakers in the industry. For more episodes of WSJ’s Tech News Briefing: https://link.chtbl.com/WSJTechNewsBriefing #AI #Regulation #WSJ

We analyze the growth of dataset sizes used in machine learning for natural language processing and computer vision, and extrapolate these using two methods; using the historical growth rate and...

Artificial intelligence raises difficult questions about who makes the call in a health crisis: the human or the machine?

Elon Musk’s automatic driving technology seems to be roughly an order of magnitude more deadly than human drivers.

The use of artificial intelligence (AI) to detect AI-generated content has gained increasing attention in recent years as the capabilities…

This is our next project.

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

Two OpenAI contractors spoke to NBC News about their work training the system behind ChatGPT.

As the companies lead the AI boom, their unconventional arrangement sometimes causes conflict.

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.

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…

I had the honor of co-organising a meeting of leading EU networks, organisations and researchers with the European Parliament on 25 May to discuss…

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.