When AI agents "go rogue," they take unintended actions to accomplish their assigned goals, often because users provided vague or conflicting instructions.

These attacks can manipulate AI behavior by hiding instructions in websites and PDFs that become part of training data. The more companies connect sites, services, and sensitive datasets to AI tools, the greater the chances of exposure to malicious code.

Most AI systems are so-called "black box" models, where we only see inputs and outputs while the inner workings remain obscure. This piece, written prior to the launch of ChatGPT, cautions developers to know why and how a system produces its results, and not to sacrifice explainability for accuracy.

Robots. Drones. Artificial Intelligence. All three are touted as potential saviors for farmers, and are already being deployed on large farms, where they assist with such tasks as managing crops, milking cows, and helping farmers make decisions about their land. But agricultural AI could have disastrous, unintended consequences.

Under human oversight, a supervising large language model interprets user tasks and delegates work to subordinate LLMs, which can generate code, fix bugs, and run tests, often most effectively for proofs of concept. Incremental backups and versioning are crucial when using such agents, which can lose details during their work as a result of compressing context history to work around memory limitations.

In 2025, readers discovered AI prompts in three writers' texts, with one even instructing the AI bot to make a passage sound more like another romance writer. This Futurism piece digs into the scandals and how it's contributed to readers' skepticism about the genre's more prolific writers.

AI hallucinations are a by-product of the sequential creation of content based on patterns in text, which may not reflect the context or meaning behind a prompt. Back-end issues like biased datasets and overfitting of model data contribute to hallucinations.

AGI incorporates sensory perception, memory, and advanced logical inference systems to move beyond the narrow tasks seen in large language models and chatbots. One of the most significant hurdles in developing AGI is designing systems that learn and can flexibly apply learning across domains.

Generative AI is the latest entry in a recurring cycle where emerging tools start as "AI" until they become common software, like databases or machine learning. Generative AI and large language models may be the next platform shift after smartphones and the Web.

Led by CEO Sam Altman, OpenAI's mission is to "ensure artificial general intelligence benefits all of humanity" by making its products open to all users. In 2023, the $86B company behind the chatbot ChatGPT consisted of a for-profit arm under its nonprofit governing board.

Many marketers argue that AI is useful in an ad agency setting. Others attribute the significant layoffs the industry has faced in recent years, at least in part, to AI. Agency leaders and big tech firms alike have supported experimenting with artificial intelligence’s capacity to create content once reserved for agency creatives.

Generative adversarial networks are a type of deep learning architecture that consists of a generator, which creates data that appear real, and a discriminator, which attempts to distinguish authentic from fake data. The two train in a competitive loop until the real and fictional data are indistinguishable.

By incorporating elements from documents such as the UN's Universal Declaration of Human Rights into a framework against which it can check its outputs, Anthropic hopes the approach will help Claude operate with good human values and behaviors beyond what human-driven training alone can provide.

A key ethical dilemma—the contemplation conundrum—explores whether implants might misinterpret mere imagination as intent to act. Neuroscientists have found no brain signal that clearly marks when someone decides to act, making intent hard to detect in neurotechnological systems.

OpenAI was originally created as a nonprofit to develop artificial general intelligence for humanity's benefit. However, skyrocketing computing costs made adherence to this belief difficult, as new influences, such as external investors, were introduced to accelerate growth with reduced safety.

As Anthropic is a public benefit corporation, its board is tasked with making sure that AI tools are developed to help people and society thrive. Members of its Long Term Benefit Trust hold no equity in the company, but make up a majority of the board and can act to maintain Anthropic's public benefit purpose.

Just as humans engage in complex behaviors to survive and reproduce, teams of experts in neuroscience, virology, mathematics, and other disciplines argue that large language models develop complex mechanisms to achieve their goals. These mechanisms can be manipulated to assess how they modify outputs—much like stimulating individual neurons—to uncover how LLMs "think."

A Freedom House report found that AI-powered disinformation campaigns and censorship tactics are spreading, with 16 countries utilizing the technology to shape online narratives or suppress dissent, as of 2023. In Venezuela, deepfake software was used to push pro-government propaganda with fake news anchors.

Analysts believe that generative AI tools—not antitrust rulings—are Google's biggest threat because they draw users away from traditional search and potential ad revenue. AI partnerships, like the one between Apple and OpenAI, may further reduce Google's market share.

Generative artificial intelligence has left no industry untouched, and banking isn’t an exception. Experts estimate that gen AI could add as much as $340B in value to the banking sector each year. For consumers, this involves new features to prevent fraud and customer service chatbots. This report dives into the revolution underway and seeks to define a “full stack” AI bank of the future. Read more here.

2022 was the year AI broke onto the scene, with applications like ChatGPT amazing users with its ability to generate realistic-sounding answers. Technologist Arvind Narayanan presents a clear-eyed view of what the technologies can (and can't) do.

An MIT study finds lower brain engagement in students who used ChatGPT, resulting in consistent underperformance in neural, linguistic and behavioral levels. AI users struggled to recall their own essays, while the brain-only group showed the highest neural connectivity and satisfaction.

Workers, particularly in marketing, are experiencing mental fatigue in the workplace due to expectations—often unspoken—that they should use AI to multitask beyond their comfort levels. Many feel they are underperforming if they don't embrace this technology. This situation differs from typical burnout. This podcast discussion suggests that this "brain fry" tends to intensify when employees are required to use more than three AI tools.

Efforts are ongoing to create artificial general intelligence, where machines outperform humans across a wide range of cognitive tasks, including those for which they have not been specifically trained. Current models utilize machine learning and neural networks to perform tasks for which they are programmed, leveraging provided training data.

Social media has become rife with misinformation. In response, some organizations have deployed AI-assisted programs trying to curb the spread of this inaccurate content. The problem is that misinformation and satire, rhetorically speaking, often use the same kind of language, something AI struggles to understand.

As AI becomes a bigger part of our lives, what does that mean for the future of humanity? The podcast Entanglements hosts a pessimistic former OpenAI employee and an optimistic Princeton professor to discuss whether AI brings dystopia or a brighter future.

As artificial intelligence (AI) becomes more widely available, journalism must adapt and establish ethical norms for how the technology is used. This report from the Center for News, Technology & Innovation looks at the issue from every angle, including legal considerations, potential biases in datasets, and the speed at which AI capabilities are changing. It also includes links to recent studies on the use of AI in journalism.

Although ChatGPT, Google's AI overviews, and other similar software can save time, a study of more than 10,000 adults showed that reliance on them yielded work products that were more generic and included fewer facts than those produced solely by Google search. Weaker brain connectivity has also been observed when users write using AI.

Ars Technica spoke with legal experts about how—and if—people could design their wills to prevent AI resurrection. Though this is not yet a common request, one lawyer suggested that people worried about living on in an AI format can draft a power of attorney and a will that prevents those in charge of one's estate from submitting any texts, voice, image, writings, or other personal information to any AI tools.

With the release of ChatGPT in 2022, which drew over 100 million weekly users in just two months, natural language processing and understanding could be achieved at scale via machine learning. Unlike earlier artificial intelligence that could pull stored knowledge, generative AI produces text, images, or sounds.

Synthetic media tools can map voices and faces to make individuals appear as someone else. Although they open the door to new opportunities in immersive education and entertainment, they also raise concerns about the misuse of personal identity.