Artificial Intelligence (AI) is a broad term with no single authoritative definition — and frequently, people mean different things when they use it.
However, AI commonly means:
The term AI is often imprecise. AI is sometimes used interchangeably with machine learning, but the two terms are not identical. Machine learning is one promising set of techniques used to develop AI, but others exist. We disambiguate machine learning and AI more fully [see the link below].
AI is also a moving target. The “AI effect” is a paradox in which problems thought to require AI, once largely solved, are no longer seen as requiring “intelligence.” This dynamic further contributes to ambiguity around the definition of AI.
—CSET Glossary, “Artificial Intelligence”
Generally, [Artificial Intelligence] constitutes a fuzzy term referring to the ability of a machine to perform cognitive functions. Approaches to AI can be subdivided into deductive—that is, model-driven (such as expert systems)—or inductive—that is, data-driven.
—CACM, “There Is No AI Without Data“
What if cybercriminals could hide pernicious payloads in places where commercial cybersecurity software were unable to detect it? Unfortunately, this approach is both possible and increasingly viable.
Hidden Malware Ratchets Up Cybersecurity Risks Read More
There is promising, if somewhat slow, progress on making facial recognition software less biased.
The Troubling Future for Facial Recognition Software Read More
Superheroes worry about having their identities revealed, while the rest of us in the real world worry about surveillance technologies and how they can be easily abused.
Modern Tech Can’t Shield Your Secret Identity Read More
The E.U. is an early mover in the race to regulate AI, and with the draft E.U. AI Act, it has adopted an assurance-based regulatory environment using yet-to-be-defined AI assurance standards.
Trust, Regulation, and Human-in-the-Loop AI: within the European region Read More
Just-in-time shipping is dead. Long live supply chains stress-tested with AI digital twins.
How AI digital twins help weather the world’s supply chain nightmare Read More
The controversy over Project Maven shows the department has a serious trust problem. This is an attempt to fix that.
The Department of Defense is issuing AI ethics guidelines for tech contractors Read More
DIU launched a strategic initiative in March 2020 to implement the DoD’s Ethical Principles for Artificial Intelligence (AI) into its commercial prototyping and acquisition programs.
Responsible AI Guidelines Read More
The U.S. Department of Defense officially adopted a series of ethical principles for the use of Artificial Intelligence today following recommendations provided to Secretary of Defense Dr. Mark T. Esper by the Defense Innovation Board last October.
DOD Adopts Ethical Principles for Artificial Intelligence Read More
Watch our (home) movie: Trillions of Questions, No Easy Answers
Trillions of Questions, No Easy Answers: A (home) movie about how Google Search works Read More
AI has not yet delivered on the promises in industry practice. The core business of industrial enterprises is not yet AI-enhanced.
We see a major need for future research regarding functional capabilities and realization technologies for an enterprise data marketplace.
We believe that deep networks excel because they exploit a particular form of compositionality in which features in one layer are combined in many different ways to create more abstract features in the next layer.
A key question for the future of AI is how do humans learn so much from observation alone?
Three key ways artificial intelligence is changing what it means to compute.
How AI is reinventing what computers are Read More
Painstaking new techniques for archiving social media posts could provide crucial evidence in future prosecutions.
The Race to Archive Social Posts That May Prove Russian War Crimes Read More
With vast amounts of data becoming available to intelligence analysts, new tools will help them sift and interpret it all—but they will introduce new risks, too.
As Russia Plots Its Next Move, an AI Listens to the Chatter Read More
The Artificial Intelligence Database: Explore the technology like never before with [WIRED’s] new database, which collects all of our stories on artificial intelligence and filters them by sector, source data, end user, company, and more.
The Artificial Intelligence Database Read More
Here, we showcase regionally developed projects that explore the use of non-traditional data sources and AI to help measure progress toward the [Sustainable Development Goals].
Non-Traditional Data Sources: Providing Insights into Sustainable Development Read More
Facebook, the Palo Alto, CA-based online social network, has teamed up with radiologists at New York University’s Langone Medical Center in Manhattan to develop an artificial intelligence (AI)-based imaging accelerator for MRI scanners.
Deep Learning Speeds MRI Scans Read More
For years, Big Tech has set the global AI research agenda. Now, groups like Black in AI and Queer in AI are upending the field’s power dynamics to build AI that serves people.
Inside the fight to reclaim AI from Big Tech’s control Read More
These recommendations are meant to increase reliability, safety, and trustworthiness while increasing the benefits of AI technologies.
Responsible AI: Bridging From Ethics to Practice Read More
The company’s AI algorithms gave it an insatiable habit for lies and hate speech. Now the man who built them can’t fix the problem. [Not because he doesn’t want to, but because he is not allowed to as it would get in the way of profits.]
How Facebook got addicted to spreading misinformation Read More