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
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.
Contact-tracing apps are fueling more AI ethics discussions, particularly around privacy. The longer term challenge is approaching AI ethics holistically.
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.
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.
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
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.
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.
More organizations are embracing the concept of responsible AI, but faulty assumptions can impede success.
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
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?
A survey shows tech leadership's growing concern about AI bias and AI ethics, as negative events impact revenue, customer losses, and more.
Biased artificial intelligence is a real issue. But how does it occur, what are the ramifications -- and what can we do about it?
Digitized presumptions, encoded by very human creators, can introduce prejudice in new financial technology meant to be more accessible.
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.
IT teams must work with managers who oversee data scientists, data engineers, and analysts to develop points of intervention that complement model ensemble techniques.