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Fragility in AIs Using Artificial Neural Networks
From Communications of the ACM

Fragility in AIs Using Artificial Neural Networks

Suggesting ways to reduce fragility in AI systems that include artificial neural networks.

Lost in Afghanistan: Can the World Take ICT4D Seriously?
From Communications of the ACM

Lost in Afghanistan: Can the World Take ICT4D Seriously?

Seeking to maximize the value of information and communication technologies for development research.

There Is Little Evidence for Today's AI Alarmism
From ACM Opinion

There Is Little Evidence for Today's AI Alarmism

Over time, we will have a much better sense of which AI areas require significant regulatory intervention and which do not.

Who Should Make the Rules that Govern AI?
From ACM Opinion

Who Should Make the Rules that Govern AI?

One question for Laura Weidinger and Iason Gabriel, research scientists at Google DeepMind.

Can Generative AI Bots Be Trusted?
From Communications of the ACM

Can Generative AI Bots Be Trusted?

It will be a long road to learning how to use generative AI wisely.

Computer-Related Risks and Remediation Challenges
From Communications of the ACM

Computer-Related Risks and Remediation Challenges

Surveying the nontechnical issues interwoven with computer-related technologies.

The Parchment Path?
From Communications of the ACM

The Parchment Path?

Is there ever a time when learning is not of value—for its own sake?

Conjoined Twins: Artificial Intelligence and the Invention of Computer Science
From Communications of the ACM

Conjoined Twins: Artificial Intelligence and the Invention of Computer Science

How artificial intelligence and computer science grew up together.

Breaking Up a Digital Monopoly
From Communications of the ACM

Breaking Up a Digital Monopoly

How to decompose a vertically integrated digital monopoly to enable competitive services based on a shared data structure.

Trust Is Not Enough: Accuracy, Error, Randomness, and Accountability in an Algorithmic Society
From Communications of the ACM

Trust Is Not Enough: Accuracy, Error, Randomness, and Accountability in an Algorithmic Society

Searching for improved algorithmic accountability.

Decentraland: The Alleged Decentralization of Blockchain Applications
From Communications of the ACM

Decentraland: The Alleged Decentralization of Blockchain Applications

Breaking down the blockchain.

Unfair Automated Hiring Systems Are Everywhere
From ACM Careers

Unfair Automated Hiring Systems Are Everywhere

The U.S. Federal Trade Commission urgently needs to regulate automated hiring systems.

When AI Thinks You Are Dead
From ACM Opinion

When AI Thinks You Are Dead

AI hallucinations can be amusing, but the consequences for society could be dangerous.

Why Conscious AI Is a Bad Idea
From ACM Opinion

Why Conscious AI Is a Bad Idea

Our minds have not evolved to deal with machines we believe have consciousness.

You Can't Regulate What You Don't Understand
From ACM Opinion

You Can't Regulate What You Don't Understand

Why AI regulations should begin with mandated disclosures.

The Indigo Cyberattack Is a Warning of Things to Come
From ACM Opinion

The Indigo Cyberattack Is a Warning of Things to Come

Those handling state secrets or critical infrastructure seem to fare no better than a bookstore chain.

AI Is Not Going to Reinvent the Alphabet Anytime Soon
From ACM Opinion

AI Is Not Going to Reinvent the Alphabet Anytime Soon

Artificial intelligence does not understand how humans read well enough to design type on its own.

AI and Politics: How Will We Know What—and Who—Is Real?
From ACM Opinion

AI and Politics: How Will We Know What—and Who—Is Real?

If we are lucky, new technologies will only cause brief confusion.

There Is No AI
From ACM Opinion

There Is No AI

There are ways of controlling the new technology, but first we have to stop mythologizing it.

AI Not Yet Intelligent Enough to Be a Trusted Research Aid
From ACM Opinion

AI Not Yet Intelligent Enough to Be a Trusted Research Aid

An attempt to use ChatGPT for scholarly research proves uncovers errors and frustration.
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