Ethics & Governance: Page

Differentiating between good and bad AI bias

As lawmakers and regulators look at ways to make machine learning models fair, some tech vendors are creating tools that aim to enable enterprises to achieve that purpose.

By Esther Shittu • Feb. 11, 2022

Nvidia, Arm deal fails after heightened regulatory scrutiny

Nvidia's acquisition of Arm Ltd. faced its share of regulatory hurdles, but the global semiconductor chip shortage prompted increased scrutiny of the chip-related deal.

By Makenzie Holland • Feb. 8, 2022

IRS facial recognition move raises bias, privacy concerns

The agency requires photo identification for certain services using a face match system from digital ID vendor ID.me, but privacy advocates say the technology is prone to bias.

By Esther Shittu • Jan. 26, 2022

Meta AI supercomputer looks toward the metaverse

The tech giant will use its new AI Research Supercluster internally for NLP and computer vision and to build new technologies for the metaverse.

By Esther Shittu , Ed Scannell • Jan. 24, 2022

Mostly AI plans to use $25M funding for responsible AI efforts

The synthetic data vendor works with customers in Europe and North America. Experts say more than half of AI projects will be created using synthetic models by 2024.

By Esther Shittu • Jan. 12, 2022

Efforts to craft AI regulations will continue in 2022

Regulating AI can be challenging for many reasons, including varying definitions of fairness and explainability. However, AI regulations will be a top focus for lawmakers in 2022.

By Makenzie Holland • Dec. 29, 2021

How an AI startup is trying to fix gender bias in the workplace

Startup Pipeline Equity provides enterprises with an AI platform to help make decisions about hiring, pay, performance, potential and promotion -- free of bias.

By Esther Shittu • Dec. 9, 2021

Microsoft unveils responsible AI guidelines and dashboard

The tech giant unveiled 10 guidelines for organizations to consider when building AI models, and a dashboard that data scientists can use to ensure their models are ethical.

By Esther Shittu • Dec. 8, 2021

FTC pursues AI regulation, bans biased algorithms

The agency tries to regulate how businesses use AI algorithms by enforcing the Fair Credit Reporting Act, Equal Opportunity Credit Act and FTC Act. Critics want more regulation.

By Esther Shittu • Oct. 19, 2021

Examining both sides of the AI regulation debate

Some government and business leaders want more AI regulation to ensure that systems don't discriminate against or harm others. Others say too much regulation will stifle innovation.

By Mark Labbe • Oct. 8, 2021

A look at AI trends and bias in AI algorithms

In the past few years, more and more organizations have focused on AI. However, just as the use of AI and machine learning has expanded, concern about AI bias is also growing.

By Esther Shittu • Sept. 23, 2021

AI carbon footprint: Helping and hurting the environment

Companies can use AI to help the environment, including by using it to prevent forest fires and reduce factory waste. At the same time, AI has its own carbon footprint.

By Lisa Morgan • Sept. 21, 2021

Expanding explainable AI examples key for the industry

Improving AI explainability and interpretability are keys to building consumer trust and furthering the technology's success.

By Kathleen Walch, Mark Labbe • Sept. 8, 2021

AI and climate change: The mixed impact of machine learning

AI can both help and hurt the environment. While companies use artificial intelligence to increase factory efficiency and lower energy costs, training AI demands a lot of energy.

By Ron Schmelzer, Mark Labbe • Aug. 31, 2021

What is data science? The ultimate guide

Data science is the process of using advanced analytics techniques and scientific principles to analyze data and extract valuable information for business decision-making, strategic planning and other uses.

By Craig Stedman • Aug. 20, 2021

AI accountability: Who’s responsible when AI goes wrong?

Who should be held accountable when AI misbehaves? The users, the creators, the vendors? It's not clear, but experts have some ideas.

By Mary Pratt • Aug. 19, 2021

Solving the AI black box problem through transparency

Ethical AI black box problems complicate user trust in the decision-making of algorithms. As AI looks to the future, experts urge developers to take a glass box approach.

By Benjamin St. George, Kassidy Kelley • Aug. 16, 2021

Building trustworthy AI is key for enterprises

Organizations need to focus on transparency in models, ethical procedures and responsible AI in order to best comply with guidelines for developing trustworthy AI systems.

By Ron Schmelzer • July 23, 2021

5 ways AI bias hurts your business

A biased AI system can lead businesses to produce skewed, harmful and even racist predictions. It's important for enterprises to understand the power and risks of AI bias.

By Mary Pratt • June 25, 2021

Combating racial bias in AI

By employing a diverse team to work on AI models, using large, diverse training sets, and keeping a sharp eye out, enterprises can root out bias in their AI models.

By Kathleen Walch • June 23, 2021

Microsoft’s acquisition of Nuance clears antitrust hurdle

The U.S. government didn't flag the Microsoft-Nuance acquisition as violating antitrust laws, but scrutiny of big tech continues as governments try to reign in powerful companies.

By Makenzie Holland • June 10, 2021

How to detect bias in existing AI algorithms

While enterprises can't eliminate bias from their data, they can significantly reduce bias by establishing a governance framework and employing more diverse employees.

By Kathleen Walch • May 6, 2021

IBM Watson updates focus on data privacy and explainability

Updates include new federated learning capabilities within IBM Watson Studio and more insights into how predictions are made in IBM Planning Analytics with Watson.

By Mark Labbe • April 21, 2021

Research manager resigns amid Google AI ethics controversy

Prominent Google AI research manager Samy Bengio resigns from the company following months of internal discord and the termination of two AI researchers.

By Mark Labbe • April 7, 2021

Synthetic data for machine learning combats privacy, bias issues

Synthetic data generation for machine learning can combat bias and privacy concerns while democratizing AI for smaller companies with data set issues.

By Lisa Morgan • March 30, 2021