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ChatGPT: How To Prevent It Becoming A Nightmare For Professional Writers

Nearly half of white-collar professionals have tried using ChatGPT to help with their work, according to a recent survey of more than 10,000 people at blue chips such as Google, JP Morgan and McKinsey. That’s staggering, considering the AI chatbot was only released to the public in November. It’s potentially very exciting for the future of work, but it also brings serious risks. ChatGPT and other imminent rivals are part of a long history of technologies geared to reducing the labour of writing. These range from the printing press to the telegram, the typewriter, word processors and personal computing. AI…

AI For The Board Game Diplomacy

Agents cooperate better by communicating and negotiating, and sanctioning broken promises helps keep them honest Successful communication and cooperation have been crucial for helping societies advance throughout history. The closed environments of board games can serve as a sandbox for modelling and investigating interaction and communication – and we can learn a lot from playing them. In our recent paper, published today in Nature Communications, we show how artificial agents can use communication to better cooperate in the board game Diplomacy, a vibrant domain in artificial intelligence (AI) research, known for its focus on alliance building. Diplomacy is challenging as it…

Self-Taught AI May Have a Lot in Common With the Human Brain

Neural networks can use self-supervised learning to figure out what matters. This process might be what helps humans do the same. FOR A DECADE now, many of the most impressive artificial intelligence systems have been taught using a huge inventory of labeled data. An image might be labeled “tabby cat” or “tiger cat,” for example, to “train” an artificial neural network to correctly distinguish a tabby from a tiger. The strategy has been both spectacularly successful and woefully deficient. Such “supervised” training requires data laboriously labeled by humans, and the neural networks often take shortcuts, learning to associate the labels with…

How The Philosophy Of Mind And Consciousness Has Affected AI Research

The “brain in a jar” is a thought experiment of a disembodied human brain living in a jar of sustenance. The thought experiment explores human conceptions of reality, mind, and consciousness. This article will explore a metaphysical argument against artificial intelligence on the grounds that a disembodied artificial intelligence, or a “brain” without a body, is incompatible with the nature of intelligence.[1] The brain in a jar is a different inquiry than traditional questions about artificial intelligence. The brain in a jar asks whether thinking requires a thinker. The possibility of artificial intelligence primarily revolves around what is necessary to make a computer…

Using Artificial Intelligence In Health Sciences Education Requires Interdisciplinary Collaboration And Risk Assessment

Over the past five years, there has been an increase in research and development related to the use of artificial intelligence (AI) in health sciences education in fields such as medicine, nursing and occupational therapy. AI-enhanced technologies have been shown to have educational value and offer flexibility for students. For example, learning scenarios can be repeated and completed remotely, and educational experiences can be standardized. However, AI’s applications in health sciences education need to be explored further. To better understand advances in research and applications of AI as a part of the education of health sciences students, we conducted a…

Delivery Robots Get Airbags To Protect You In Case Of Collision

But do they actually work? utonomous vehicle maker Nuro has added external airbags to its self-driving delivery robots to protect pedestrians — but there’s reason to be skeptical about their effectiveness. Drivers wanted: During the pandemic, more people started ordering their food, groceries, and other goods for delivery rather than venturing into stores and restaurants for them. This has led to an increased demand for delivery drivers that companies have had trouble meeting. “There is no store in the country right now with enough delivery drivers,” Dennis Maloney, chief digital officer at Domino’s Pizza, told AP News in November 2021. “[The airbag] is optimized to reduce…

How To Handle Imbalanced Data In Machine Learning Classification

In this tutorial, you’ll learn about imbalanced data and how to handle them in machine learning classification in Python. Imbalanced data occurs when the classes of the dataset are distributed unequally. It is common for machine learning classification prediction problems. An extreme example could be when 99.9% of your data set is class A (majority class). At the same time, only 0.1% is class B (minority class). Suppose you throw such data directly into machine learning algorithms. You may find the model ‘ignores’ the minority class and gives wrong predictions of it. It is frustrating since the goal is often to predict the minority…

How Companies Are Actually Using AI In Everyday Practices

When thinking of AI (artificial intelligence), mixed emotions often come to mind. For movie buffs, we might immediately see images of Will Smith battling it out with humanoid AI creatures in IRobot or the even more realistic looking depiction of artificial intelligence in the movie aptly called AI. In our human minds, AI is something that could potentially lead to a catastrophic apocalypse as machines take over the world. This is not just hearsay as with some things. According to a recent study about AI and marketing, 2,000 Americans were asked what they thought the potential impact of machines learning…

Explainable AI May Surrender Confidential Data More Easily

Researchers from the National University of Singapore have concluded that the more explainable AI becomes, the easier it will become to circumvent vital privacy features in machine learning systems. They also found that even when a model is not explainable, it’s possible to use explanations of similar models to ‘decode’ sensitive data in the non-explainable model. The research, titled Exploiting Explanations for Model Inversion Attacks, highlights the risks of using the ‘accidental’ opacity of the way neural networks function as if this was a by-design security feature – not least because a wave of new global initiatives, including the European Union’s draft AI regulations, are characterizing explainable…

7 Ways To Make The Wider Enterprise Comfortable With Artificial Intelligence

The challenge is putting people first in any and all AI projects. AI practitioners provide recommendations for building a people-centric, yet AI-driven culture. As the people charged with designing, building, and deploying artificial intelligence — from data engineers to developers — recognize, AI is a powerful mechanism for amplifying human knowledge, skills, and efficiency. But how can AI proponents employ AI to fix a moribund or toxic corporate culture? That’s probably the most vexing challenge with AI rollouts. Entrepreneurs and experts at the front lines of the AI revolution recognize this is a hurdle technology alone can’t solve, “AI cannot…

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