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Common AI Ethical Mistakes Businesses Makes

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As organizations are embracing AI, faulty mistakes can cost them, if not corrected.

Ethical artificial intelligence and responsible artificial intelligence are what every industry is talking about. The majority of the companies are looking for a course correction to practice trustworthy AI processes. But where do they start?

It’s understandable that companies don’t intend to do unethical things with artificial intelligence. But when something goes wrong, customers and stakeholders care less about the company’s intentions and more about the result of the disruptive technology. So, here are a few reasons why companies are struggling with responsible AI.

1. Too Much Focus On Algorithms

For many business owners, it has become a brand issue. Hence, they’re more concerned about algorithm bias, forgetting the fact that artificial intelligence requires more.

“An artificial intelligence product is never just an algorithm. It’s a full end-to-end system and all the related business processes”, says Steven Mills, Managing Director, Partner, and Chief AI ethics officer at Boston Consulting Group (BCG). “You could go to great lengths to ensure that your algorithm is as bias-free as possible but you think about the whole end-to-end value chain from data acquisition to algorithms to how the output is being used within the business.”

2. Unrealistic Expectations

While many companies have adopted responsible artificial intelligence values, they are expecting too much out of it like a marketing tactic. Principles and values depict the belief system that’s a part of responsible artificial intelligence. But companies are not using artificial intelligence systems for anything real.

“Part of the challenge lies in the way principles get articulated. They’re not implementable”, said Kjell Carlsson, principal analyst at Forrester Research who writes about data science, machine learning, advanced analytics, and artificial intelligence. “They’re often at such an aspirational level that they often don’t have much to do with the topic at hand.”

3. Companies Have Separated Responsible Artificial Intelligence Processes

Ethical AI is viewed as a separate category like cybersecurity which is wrong. Responsible artificial intelligence cannot work in singularity. Responsible AI needs to become a natural part of the product development team’s working which will result in less resistance which otherwise will be understood as another risk function in the business.

4. Companies Create An AI Board Without A Plan

Ethical AI boards are necessary for a company, true, but without a plan, it will all fall down. Companies need to understand artificial intelligence’s impact from legal, business, ethical, technological, and other standpoints to think about what can go wrong and what the consequences can be.

It is important to carefully select who will serve on the board because there is a chance to receive political bias. For instance, Google dissolved its AI ethics board after just one week because it received a complaint about one of its members being anti-LGBTQ. Another person was also reported in the team who was a CEO of a drone company that was using AI for military applications. This can happen when boards are formed with an adequate understanding of who should take up important roles.

Clearly, there’s more to AI that companies understand. Adopting AI is an immersive task that requires planning, good leadership, fair implementation, and evaluation that is enabled by technologies and people. Companies should have a plan and strategy to introduce responsible AI and the impact it can have on change.

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