Artificial intelligence (AI) technologies are more popular than ever. However, they are more than a shiny new toy. ZD Net brought this interesting subject to our attention in their article, “Artificial intelligence: Everyone wants it, but not everyone is ready.“
Often times as with anything innovative, people get a little distracted by the new technology. Big data was distracting for a long time, but now the conversation has shifted.
AI has captured the public’s imagination for some time, and businesses are currently grappling with how it can be integrated into their organization. In fact, AI has become so prolific, the EU has recently set a series of new rules that seek to regulate how businesses use the technology.
There’s still much work to be done and it comes down to the people that can make AI happen, and make it as fair and accurate as possible.
This depends on organizations understanding how AI systems make the decisions they do, and as a result, how the results are being applied. Explainable AI is used to describe an AI model, its expected impact and potential biases. Explainability becomes critical when the results can have an impact on data security or safety.
Melody K. Smith
Sponsored by Access Innovations, changing search to found.
