There are not one but two dimensions of bias that can be revealed through the study of large AI models: not only bias in training data or the products of an AI, but also bias in society, such as disparity in employment or health outcomes between different demographic groups. Often training data and AI output is biased for or against certain demographics (i.e. older white people are overrepresented in image datasets), but sometimes large AI models accurately illustrate biases in the real world (i.e. young black men being disproportionately viewed as threatening). These social disparities often appear in image generation AI outputs in the form of 'marked' features, where some feature of an individual or setting is a social marker of disparity, and prompts both humans and AI systems to treat subjects that are marked in this way as exceptional and requiring special treatment. Generative AI has proven to be very sensitive to such marked features, to the extent of over-emphasising them and thus often exacerbating social biases. I briefly discuss how we can use complex prompts to image generation AI to investigate either dimension of bias, emphasising how we can probe the large language models underlying image generation AI through, for example, automated sentiment analysis of the text prompts used to generate images.

At leading Swedish university Lund, teachers decide which students can use artificial intelligence to help them with assignments. At the University of Western Australia in Perth, staff have talked to students about the challenges and possible benefits of using generative AI in their work, while the University of Hong Kong is allowing ChatGPT within strict limits. Launched by Microsoft-backed OpenAI on Nov. 30, ChatGPT has become the world's fastest growing app to date and prompted the release of rivals like Google's Bard.

A young boy communicating with a robot that is on display at Incheon International Airport in Seoul ... [ ] / South Korea. Artificial Intelligence is going to transform the world, changing a lot of things for all categories of people in the process; children will be among the most affected. "You and I live in an age where we're starting to be impacted, but we've spent a lot of our lives not really having interacted with AI. We're also adults that have some volition and agency. For children, it's different," Erica Kochi, co-founder of UNICEF Innovation Unit, tells me.

A work made by AI image generation, part of the'Promptism' art movement, reflecting on a new generation merged with Artificial Intelligence, that we now witness its emergence. Inspired by sci-fi stories, visions of the future, acceleration of technology, and sense of apocalypse. Where will it all take us? A work made by AI image generation, part of the'Promptism' art movement, reflecting on a new generation merged with Artificial Intelligence, that we now witness its emergence. Inspired by sci-fi stories, visions of the future, acceleration of technology, and sense of apocalypse.

If I could tell you how you could make your AI system do nearly ten times as much work on the same hardware, would that be worth something to you, eh…? So how can we make our AI ten times more efficient? Well, compression of data can help us store more in a fixed space, so let's start there. Popular compression technologies for digital media (think .mp3, There is information in the signal that can be isolated. If we just focus on the parts with the greatest information content, we can throw away the rest and get a vastly smaller file.

Can AI function like a human brain? But now, armed with Neuromorphic Computing, they are ready to show the world that their dream can change the world for better. As we unearth the benefits, the success of our machine learning and AI quest seem to depend to a great extent on the success of Neuromorphic Computing. The technologies of the future like autonomous vehicles and robots will need access to and utilization of an enormous amount of data and information in real-time. Today, to a limited extent, this is done by machine learning and AI that depend on supercomputer power.

On 6-7 May 2019, the World Economic Forum Centre for the Fourth Industrial Revolution and its partners UNICEF and the Canadian Institute for Advanced Research (CIFAR) hosted a workshop in San Francisco on the joint "Generation AI" initiative. This workshop identified deliverables in two key areas: 1) public policy guidelines that direct countries on creating new laws focused on children and 2) a corporate governance charter that guides companies leveraging AI to design their products and services with children in mind.

A young boy communicating with a robot that is on display at Incheon International Airport in Seoul / South Korea. Artificial Intelligence is going to transform the world, changing a lot of things for all categories of people in the process; children will be among the most affected. "You and I live in an age where we're starting to be impacted, but we've spent a lot of our lives not really having interacted with AI. We're also adults that have some volition and agency. For children, it's different," Erica Kochi, co-founder of UNICEF Innovation Unit, tells me.

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In a multi-year initiative, the team will consult experts across relevant fields (ranging from psychology, to industrial design, to AI science, to technology law, etc.) through formal desk research (including a dedicated Masters course at UC Berkeley and an evidence review by Baker Mckenzie), phone interviews, workshops, etc. to fill in the gaps in evidence where it is most needed to further child rights in the context of the extremely far reaching, fast-paced, and in some cases unpredictable, development of AI technologies. We will strengthen our formal research with collected insights from children relaying their hopes, worries, and visions for how technology may impact their lives. Taken together, this work will inform sets of actionable, specific recommendations for governments, companies, and caregivers that we will stress test before striving to implement through strategic partnerships.