Machine Learning

City builds a future-facing tech foundation

Coral Gables, Florida, wants its applications to be state-of-the-art, evergreen, user-centric, cloud-based, mobile-accessible and horizontally integrated.

  • By Stephanie Kanowitz

How AI could take over elections – and undermine democracy

An AI-driven political campaign could have grave implications for election outcomes as algorithms manipulate the messages and advertisements individuals see to ultimately sway their voting behavior, experts warn.

  • By Archon Fung and Lawrence Lessig, The Conversation

How agencies can automate data extraction at scale

COMMENTARY | By combining optical character recognition technology with machine learning, agencies can leverage their unstructured data more easily to improve efficiency, reduce backlogs and solve operational challenges.

  • By Matt Macnak

Metadata catalog refreshes one state’s water use insights

A metadata catalog is helping Arizona water resource managers quickly find and analyze the data needed by water users, planners and decision-makers.

  • By Susan Miller

How agencies can clean up criminal records to automate expungement

Automatic record clearance is a growing priority for states as criminal records delay individuals’ ability to reenter society and fill open job slots.

  • By Kaitlyn Levinson

AI project targets hidden tax shelters

By flagging unintended consequences of changes to tax policies, AI researchers hope to shut down tax shelters used by sophisticated tax dodgers.

  • By Stephanie Kanowitz

Takeaways from our investigation into Wisconsin’s racially inequitable dropout algorithm

Wisconsin’s Dropout Early Warning System (DEWS) scores every middle schooler based on income, race and more.

  • By Todd Feathers, The Markup

AI/ML advancements outpacing government policies, cyber experts warn

National security, emerging technology and cybersecurity experts told lawmakers Wednesday that the federal government must implement new guardrails to cope with recent advancements in artificial intelligence and machine learning.

  • By Chris Riotta

Robots are everywhere – improving how they communicate with people could advance human-robot collaboration

Rapid tech advancements could set humans and robots up for collaborative work in agriculture, medical care and other fields.

  • By Ramana Vinjamuri, The Conversation

Don’t bet with ChatGPT – study shows language AIs often make irrational decisions

Generative AI models don't always make rational choices, experts say.

  • By Mayank Kejriwal, The Conversation

AI information retrieval: A search engine researcher explains the promise and peril of letting ChatGPT and its cousins search the web for you

Generative artificial intelligence may seem like a convenient solution to a quick query, but users should caution the potential for unverified or even false responses.

  • By Chirag Shah, The Conversation

Machine learning too expensive for state archives – for now

The Oregon State Archives will pivot from machine learning to advanced analytics for streamlining management of several terabytes of new data.

  • By Chris Teale

We pitted ChatGPT against tools for detecting AI-written text, and the results are troubling

The race between tools that generate artificial intelligence-enabled text and the tools to detect nonhuman writing has no clear winner.

  • By Armin Alimardani and Emma A. Jane, The Conversation

Machine learning maps location of lead pipes

An open-source map will help communities find and remove pipes faster.

  • By Kaitlyn Levinson
Featured eBooks

When data science shortcuts are a bad idea

Auto-ML can help non-data scientists write programs, but the resulting applications may be flawed, biased or useless, an expert says. Still, agencies can minimize risk and optimize the use of citizen data scientists.

  • By Stephanie Kanowitz

10 steps to future water sustainability

Municipal water managers can harness new technologies that will adapt to changes in how water is understood, managed and shared.

  • By Stephanie Kanowitz

Philosophers have studied ‘counterfactuals’ for decades. Will they help us unlock the mysteries of AI?

One expert discusses the importance of explainable artificial intelligence to not only guide decision-making, but provide explanations behind an algorithm's outcome.

  • By Sam Baron, The Conversation

Facial recognition: Can fake data produce real results?

Diversifying training datasets with computer-generated faces may help break down bias in the technology, but one expert says using synthetic images is a step too far.

  • By Kaitlyn Levinson

Flood forecasts in real-time with block-by-block data could save lives – a new machine learning method makes it possible

A sophisticated flood model can be used to train local flood hazard models that can pinpoint conditions street by street using real-time storm forecasts.

  • By Valeriy Ivanov, The Conversation

AI might be seemingly everywhere, but there are still plenty of things it can’t do – for now

Artificial intelligence remains a powerful tool for analytic and predictive capabilities, but just interpreting data is not enough to put AI on the same level of human thinking, one expert says.

  • By Marcel Scharth, The Conversation

Can machine learning predict the next big disaster?

Combining statistical algorithms with machine learning allows for accurate extreme weather predictions without the need for massive amounts of historical data, a new study found.

  • By Brown University, Futurity