Quick Study: Artificial Intelligence Ethics and Bias

Our collection of articles will help guide you through why organizations need an AI ethics strategy, what’s a good and bad ethics strategy, and how and why to tackle bias head on.

James M. Connolly, Contributing Editor and Writer

May 31, 2022

4 Min Read
quill pen writing the word ethics
Wavebreakmedia Ltd FUS5

Mention artificial intelligence to pretty much anyone and there's a good chance that the term that once seemed magical now spawns a queasy feeling. It generates thoughts of a computer stealing your job, technology companies spying on us, and racial, gender and economic bias.

So, how do we bring the magic back to AI? Maybe it comes down to people and things that humans actually do pretty well: thinking and planning. That's one finding that will become clear in a review of the articles in this Quick Study packed with InformationWeek articles focused on AI ethics and bias.

Yes, there are ways to develop and utilize AI in ethical manners, but they involve thinking through how your organization will use AI, how you will test it, and what your training data looks like. In these articles AI experts and companies that have succeeded with AI share their advice.

Why You Need an Ethics Strategy

What You Need to Know About AI Ethics

Honesty is the best policy. The same is true when it comes to artificial intelligence. With that in mind, a growing number of enterprises are starting to pay attention to how AI can be kept from making potentially harmful decisions.

Why AI Ethics Is Even More Important Now

Contact-tracing apps are fueling more AI ethics discussions, particularly around privacy. The longer term challenge is approaching AI ethics holistically.

Data Innovation in 2021: Supply Chain, Ethical AI, Data Pros in High Demand

Year in Review: In year two of the pandemic, enterprise data innovation pros put a focus on supply chain, ethical AI, automation, and more. From the automation to the supply chain to responsible/ethical AI, enterprises made progress in their efforts during 2021, but more work needs to be done.

The Tech Talent Chasm

How a changing world is forcing businesses to rethink everything, and in recruiting IT talent understand that great candidates want their employers to take AI ethics seriously.

3 Components CIOs Need to Create an Ethical AI Framework

CIOs shouldn’t wait for an ethical AI framework to be mandatory. Whether buying the technology or building it, they need processes in place to embed ethics into their AI systems, according to PwC.

Ethics Strategy Done Right, or Wrong

Why You Should Have an AI & Ethics Board

Guidelines are great -- but they need to be enforced. An ethics board is one way to ensure these principles are woven into product development and uses of internal data, according to the chief data officer of ADP.

How and Why Enterprises Must Tackle Ethical AI

Artificial intelligence is becoming more common in enterprises, but ensuring ethical and responsible AI is not always a priority. Here's how organizations can make sure that they are avoiding bias and protecting the rights of the individual.

Common AI Ethics Mistakes Companies Are Making

More organizations are embracing the concept of responsible AI, but faulty assumptions can impede success.

How IT Pros Can Lead the Fight for Data Ethics

Maintaining ethics means being alert on a continuum for issues. Here’s how IT teams can play a pivotal role in protecting data ethics.

Taking Bias to Task

Ex-Googler's Ethical AI Startup Models More Inclusive Approach

Backed by big foundations, ethical AI startup DAIR promises a focus on AI directed by and in service of the many rather than controlled just by a few giant tech companies. How do its goals align with your enterprise's own AI ethics program?

The Cost of AI Bias: Lower Revenue, Lost Customers

A survey shows tech leadership's growing concern about AI bias and AI ethics, as negative events impact revenue, customer losses, and more.

What We Can Do About Biased AI

Biased artificial intelligence is a real issue. But how does it occur, what are the ramifications -- and what can we do about it?

How Fighting AI Bias Can Make Fintech Even More Inclusive

Digitized presumptions, encoded by very human creators, can introduce prejudice in new financial technology meant to be more accessible.

I’m Not a Cat: The Human Side of Artificial Intelligence

Unconscious biases will be reflected in the data that feeds your AI and ML algorithms. Here are three simple actions to dismantle unconscious bias in AI.

When A Good Machine Learning Model Is So Bad

IT teams must work with managers who oversee data scientists, data engineers, and analysts to develop points of intervention that complement model ensemble techniques.

About the Author(s)

James M. Connolly

Contributing Editor and Writer

Jim Connolly is a versatile and experienced freelance technology journalist who has reported on IT trends for more than three decades. He was previously editorial director of InformationWeek and Network Computing, where he oversaw the day-to-day planning and editing on the sites. He has written about enterprise computing, data analytics, the PC revolution, the evolution of the Internet, networking, IT management, and the ongoing shift to cloud-based services and mobility. He has covered breaking industry news and has led teams focused on product reviews and technology trends. He has concentrated on serving the information needs of IT decision-makers in large organizations and has worked with those managers to help them learn from their peers and share their experiences in implementing leading-edge technologies through such publications as Computerworld. Jim also has helped to launch a technology-focused startup, as one of the founding editors at TechTarget, and has served as editor of an established news organization focused on technology startups at MassHighTech.

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