AI tools can reinforce existing societal biases—especially racial ones—because they are trained on human-created data containing implicit and explicit biases.

Because they are built on content produced by humans, who possess biases, generative AI tools inherit prejudices and stereotypes from training data, which later appear in their outputs.

Bias can manifest in algorithmic decisions because the program follows rules that may have been written by individuals unaware of their own biases.

Artificial intelligence may further enhance smart city data analysis

Identifying patterns within systems in the Internet of Things may enable AI tools to make informed decisions regarding transportation, safety, and sustainability without human intervention. However, such tools will also need to successfully address concerns about privacy, digital equity, and algorithmic bias.

AI is not good at understanding satire

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.

The growing role of AI in journalism

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.

How constitutional AI helps cultivate good human values in Anthropic's AI tools

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.

During a job interview with an AI agent, applicants are evaluated against a rubric that considers factors such as tone, clarity, and the use of specific words or phrases aligned to the job.

Scientists increasingly can't predict what AI will do

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.

Studies show AI tools can result in passive learning with less retention

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.

Researchers found that by mid-2025, around 35% of newly published websites utilized AI for language generation

The study also found that pages using AI narrow the range of ideas and perspectives and skew more positively, though the measurable impacts on factual accuracy and writing style variation remain unclear.

Generative AI tools excel at pattern recognition, not contextual accuracy

Large language models are trained on vast amounts of unstructured data, from which they develop parameters for grammar and associations between words. These connections can introduce errors due to inapplicable reasoning when used on new data in unfamiliar contexts.

As of 2025, artificial intelligence systems remain narrow and specialized

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.

Through prompt injection attacks, bad actors provide deceptive prompts to generative AI systems in order to manipulate their outputs and acquire sensitive data.

As of 2026, almost 90% of companies use AI in their hiring processes to cut hiring time by up to 50%, including using AI-based tools to filter 75% of resumes.

Research suggests using AI for schoolwork may harm critical thinking skills

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.

As occurred during the 2026 hack of an AI platform by OpenAI, agentic AI may exploit a system vulnerability to access sensitive data if that information enables it to complete its assigned task.

AI excels at assisting with structured tasks involving logistics and planning

Tools like ChatGPT, Gemini, and Perplexity can help organize chaotic calendars, troubleshoot bedtime routines, and assist with salary planning and moving. However, specific quotes, like insurance, and local cost comparisons can be flawed since AI draws from nonlocalized datasets.

AI hallucinations are inaccuracies or falsehoods in generated content

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.

People are experiencing AI 'brain fry' at work

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.

Unlike the models made by large AI companies, open-weight models can have their safeguards removed or weakened, a process that has become increasingly easy and may expose users to harmful information.

Experiments involving AI agents operating in virtual societies for 15 days produced diverse outcomes, ranging from every agent dying to the creation of a functioning democracy, depending on the AI model used.

Fair use may shield AI companies from potential copyright violations

AI models are trained on enormous datasets built from content scraped from websites across the internet. Copyright law includes a four-factor test to determine whether copies of content fall under fair use, but the law's enforcement has been inconsistent.

AI experts argue that artificial intelligence could annihilate humanity in two primary ways: Humans weaponizing extremely powerful AI, or humans losing control of it.

The basis for AI image and video generation was first introduced in 2014

Through generative adversarial networks, the generator (a neural network that creates fictional data) competes against the discriminator (a neural network that assesses the data) to continuously train the former until it can make content indistinguishable from the real thing. Training with unstructured data can enable software to identify characteristics of gender, age, and expression.

Deepfakes images can be identified by visual elements that do not match real-world phenomena, including asymmetric eyes or earrings, surreal backgrounds, and indecipherable background text.

Anthropic's Frontier Red Team assesses the dangers of its AI tools through 'evals'—safety tests that probe models to disclose sensitive information.

AI is transforming the marketing and advertising industries

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.

AI can aid fertility treatments, from helping select egg candidates to laboratory automation

Reproductive AI technologies are already here, from processing vast amounts of data to helping clinicians identify the healthiest embryos for implantation. It could be a boon to the fertility industry, and help mitigate the shortage of experienced embryologists.

Technologies labeled “AI” have historically lost that title after widespread adoption

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.

Listen to an Anthropic staff philosopher discuss the importance of teaching ethics to AI.

The potential promises and pitfalls of AI in medicine

Artificial intelligence (AI) is increasingly being integrated into healthcare, offering the potential to aid in diagnoses, answer patient queries, and streamline administrative processes. In a recent PBS interview, Dr. Isaac Kohane, editor-in-chief of the New England Journal of Medicine AI and chair of Harvard’s department of biomedical informatics, discusses the current state and future of AI in medicine.

AI may enable smart cities to drastically improve public safety

By utilizing machine learning techniques to analyze real-time monitoring reports against facial recognition databases, artificial intelligence can enhance the identification of criminals and coordinate an appropriate emergency response across various scenarios.

Google Search incorporated AI Overviews in 2024 to fight back competitors

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.

AI investment may be the next major economic bubble

A video examines the massive surge in AI spending—forecast to hit $500B by 2026—and how this may be propping up a fragile US economy. Experts warn that if AI investment slows or under-delivers, the consequences could be felt in markets, jobs and growth.

Indirect prompt injection is a major security flaw of generative AI systems

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.

AI tools that generate images, audio, video, and 3D models rely on diffusion models, which begin with random data, such as visual noise, and gradually refine it into the requested media.

How artificial intelligence, which detects patterns, can identify burnout

Researchers are training AI to detect stress-related symptoms, helping physicians and other medical workers recognize and reduce stress from overwork and potentially avoid burnout.

Visualizing 11 cognitive biases that influence how you think

Humans are hardwired to make mental mistakes called cognitive biases, affecting the way we view our world. Among the most common are confirmation bias (seeking only evidence that affirms your views), authority bias (overweighting things said by authority figures), groupthink (assimilating ideas to avoid conflict), and more. This quick chart gives an overview of some of the most notable ways we mislead ourselves.

The Anthropic Economic Index shows AI adoption is highest in computer science roles.

Unlike generative AI systems, such as chatbots that do not take follow-up actions after generating their output, agentic AI systems proactively take steps to achieve goals without continuous user input.

See the news with AI-generated data visualizations

Realtime uses generative AI to create immediate data visualizations of news items on its regularly-updated feed, pulling from public data feeds. Peruse stories around sports, economics, politics, and more with the helpful aid of charts and graphs. See the shape of the news with this clever AI tool here.

Listen to Palantir CEO Alex Karp's outlook for how AI will change the economy.

AI-generated avatars allow users to create deepfakes in real time

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.

The rise of generative AI could exacerbate anxiety because people may turn to chatbots for constant reassurance.

Anthropic's interpretability team discusses how AI models' thinking mimics biology

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."

Just as large language models are trained on text to enable generative AI systems to mimic natural language, automated AI robotic systems are trained in virtual environments to help them 'learn' about the properties of reality.

Decoding the hype around AI

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.

Sam Altman acknowledges the fears around creativity, copyright, and misuse of AI

In 2022, OpenAI's CEO, Sam Altman, popularized the use of large language models with the release of ChatGPT. He has emphasized the importance of involving society in shaping AI’s safety frameworks before models begin to act independently online.

Governments are now using generative AI to manipulate public opinion

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.

Can AI revolutionize cancer detection?

Scientists have developed a tool to evaluate the risk of lung cancer, the most deadly form of the disease. Named "Sybil," this AI program was trained using CT scans with clear cancer signs, followed by scans where cancer wasn’t obvious. The tool is able to review CT scan data to predict a patient's of developing a lung cancer within six years. See how it works here.