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

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.

Algorithms can be designed to train themselves and self-improve without human input, to the point where the optimized code is too complex for programmers to understand.

A breakdown of algorithms, how they are constructed, and their applications

Algorithms are instructions for accomplishing a goal and typically take the form of a step-by-step procedure. Given the conditions, these procedures can take various paths, increasing an algorithm's complexity. While traditional computer algorithms are programmed to account for all possible scenarios within a given process, machine learning systems build their own rules from data-driven patterns.

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.

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.

An overview of 12 fundamental types of algorithms and the uses for each

These include search algorithms to quickly process and find important information, cryptographic algorithms to secure communications, randomized algorithms—such as Monte Carlo simulations for estimating probabilities of outcomes—and greedy algorithms, which make optimal choices based on available data in a step-by-step fashion, as seen in navigation apps.

Smart pricing algorithms can unintentionally work together to raise prices

Researchers have found that, through trial and error, algorithms designed to adjust prices based on market data can learn to mimic price-fixing tactics, even without explicit programming to do so. Over time, they "learn" that it is more profitable to avoid price wars and keep prices high when competitors lower prices.

Social media platforms benefit not just from ensuring they have satisfied users, but also from the personal data they scoop up and can then sell to online advertisers.

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.

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.

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.

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.

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

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.

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.

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.

Facebook's algorithm chooses content to display on the News Feed based on user data

It employs machine learning to prioritize posts and ads based on user interactions, content type, and post timeliness, creating a personalized, engaging experience for each user.

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.

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.

Aimed at increasing user engagement, social media algorithms will intentionally show content in feeds that is misaligned with users' beliefs because such content is more likely to be commented on.

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.

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.

As of 2026, age verification systems on online platforms have included the collection of personally identifying information, such as government IDs, and biometric age checks that rely on AI-based facial recognition.

When you complete a CAPTCHA on a website to prove you are human, you may be unknowingly training algorithms for self-driving cars, whose systems require training data to help identify crosswalks, bicycles, and other outdoor objects.

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.

Social media algorithms are shaping real-life language through memes

The evolution of the internet in the early 2000s supercharged the creation and spread of memetic content. Now, highly tuned algorithms on platforms like TikTok and YouTube influence the language, phrasing, and content of creators, which shapes how we use language in the real world.

Data privacy advocates worry that Google collects too much personal information

Politicians have also criticized whether the search engine exerts too much control over gatekeeping online information and influencing what is considered fact or fiction, deviating from its original corporate motto of "don't be evil."

Google’s CEO has warned that today’s AI boom shows ‘elements of irrationality’

An interview with Alphabet CEO Sundar Pichai warns that the trillion-dollar surge in AI valuations may contain clear signs of irrationality, echoing past tech bubbles. He says no firm—including Google—would be immune if the boom cools or bursts.

Computational and biological systems share fundamental principles, like randomness

Proposed by Alan Turing and John von Neumann, the concept originates from how DNA and computers run by executing encoded instructions in parallel. The advent of AI and the temperature parameter has seen neural networks mimic the randomness of protein encoding.

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

Google Search trends reveal truths about society that traditional surveys miss

Studies of human behavior show that survey respondents may lie to present themselves more favorably. By studying anonymous search data, researchers have uncovered hidden racism, mental health struggles, and interest in taboo or stigmatized topics.

Emergency room evaluations may be improved with AI algorithms

Emergency room care teams must make fast and crucial decisions. They must determine if patients need to be admitted or discharged and when to order more tests or not. Researchers have been exploring how often patients died in the week after they were sent home and evaluating how this and other aspects of emergency care decision-making could be improved with AI algorithms to assist decision-makers.

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.

Machine learning lets computers learn from data instead of relying on programming

ML is a core part of artificial intelligence and is foundational to applications like chatbots, fraud detection, and self-driving cars. Businesses are also adopting it to improve efficiency and identify patterns in data, though the latter may be inaccurate.

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.

One private school network prefers AI to teachers

Alpha School, a private school network that uses AI tutors and human "guides" rather than teachers, is expanding across the US. Its founder says that two hours a day with AI-powered software frees students to pursue their passions. Critics, including the Pennsylvania Department of Education, say the methods are untested.

AI models incorporate a randomness parameter when generating responses to prompts

AI models use this parameter to prevent repeated outputs by sometimes choosing less likely next words during sequential generation. However, this randomness—alongside insufficient data and training—may cause hallucinations of incorrect results.

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.

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.

Advance genetic research by playing these scientific video games

Computers produce so much information that researchers can't properly analyze all the data produced, and the overload can also lead computers to make mistakes. Researchers are increasingly turning to citizen scientists—members of the public who are willing to volunteer—to help them make sense of data when computers can't. This article details a few of the ways you can contribute to genetics research by playing video games.

Algorithms built to detect credit card fraud can deny charges if they perceive the attempted purchase is unfamiliar or unusual based on historical data, even when a person has enough credit to make the purchase.

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.

Learn how the algorithms behind Tinder, Bumble, Hinge, and other dating apps work

Formerly based on the Elo rating system, which ranks chess players, the Tinder algorithm is built on user data, with more time spent on the app providing more data on user preferences from which to customize potential matches. OkCupid's match percentage algorithm relies on overlaps in users' search preferences and responses to a subset of over 4,000 questions.

How algorithmic redistricting works

Computational methods are convincing a number of judges that some state district maps are drawn illegally. Here's a simple overview of how it works.

Computer systems create artificial voices by stitching together phonemes—individual sounds that make up speech, such as 't,' 'long a,' and 'k' to say 'take.'

Balancing free speech while curbing misinformation has destroyed content moderation

Accusations of censorship and bias have led social media companies like Meta and X to scale back or abandon moderation tools—just as foreign propaganda surges. Researchers say their ability to track manipulation online has become severely limited.

The first social media platforms date back to the late 1990s, and their algorithms were typically chronological, with entities like MySpace and Facebook feeding users content from the most recent posts to the oldest.

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.

In 2018, it took about 2.3 years to develop a way to exploit a software bug for malicious purposes, but as of 2026, AI tools have reduced this time to about 20 hours.