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.
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