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Is this AI biased?

AI is a game-changing technology for companies, but it can go terribly wrong.

As AI-based systems become more critical to companies, we all need to understand the issue of bias in AI. The biases of AI can result in reputational risk, poor results and outright errors. This article will enable boards and senior executives to ask the right questions about the five dangerous biases of AI.

1) Human Bias

One reason bias exists in an AI-based system is that the data we feed AI systems is biased. …

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I’m not a very good poker player. (That’s why my friends always invite me to play.) They like to play until the winner takes all of the winnings, which ultimately includes all my money. I’m OK with this because it’s only a small game, and for me, it’s worth the price of admission.

Now shift your thinking to the business world. Imagine running a business where your main competitor has the dominant market share, and you are in second place. …

Most people are familiar with deepfake videos where it appears that a person is doing and saying things they actually never did or said. As the AI technology behind deepfakes becomes better and better, so do the results of deepfake creations.

Recent advances in this AI-based technology are happening so quickly, that it is becoming fairly easy and cheap to make high quality deepfakes. Deepfakes are created by AI that continually tests the results of a video, audio and/or text until they reach a “realism” threshold. …

Source: SP Global

As a senior executive, you’re likely aware of the many strategic opportunities and threats posed by AI. According to IDC, spending on AI hardware and software is increasing at a CAGR of 24%. AI-driven projects will rapidly become a substantial percentage of any company’s investment in technology.

What you may not be aware of are the environmental impacts of AI. AI can contribute to your company’s carbon footprint or if managed well, help reduce the impact your company has on the environment.

The issue of environmental sustainability is becoming a more critical issue to CEOs and boards as the finance…

The current economic environment enables many large companies to succeed, while many small and medium businesses (SMBs) are suffering. Adding to this divide are the changes created by AI. Right now, larger companies are investing in AI because they recognize the opportunity to dominate a market using this technology.

Big companies have many advantages when it comes to AI. They have more data (a critical factor for success), more talent, more opportunities for improvement, and more investment capital. If you are running an SMB, how can you possibly compete against these larger companies using AI?

Fortunately, SMBs can leverage AI…

This recession is deeper and more sudden than any other we have experienced. While we would all prefer this recession be a short one, that is currently unlikely. A deep and prolonged recession puts tremendous pressure on CEOs and Boards of all but the most fortunate companies.

Let’s assume this recession will last longer than we would like. In this recession, some companies will emerge as winners and many companies will fail. How can AI help? Why would senior executives even think about AI at a time like this? Why invest now?

AI is more important, and more transformative, than…

Photo credit: CloudMinds

Within the US, we are experiencing an increase in COVID-19 cases and the loss of permanent jobs. While the June employment numbers look very promising (the number of jobs increased by 4.8 million), they hide two important factors. The first is that these numbers came out just before the explosion in cases. The second is that many of these jobs are only part-time, instead of the full-time jobs that existed before the pandemic.

From a policy perspective, we’d like to see businesses accelerate their return to normalcy and we’d like to see unemployment go down. …

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IBM just got out of the business of facial recognition software. Microsoft and Amazon have limited what they are doing with facial recognition with law enforcement agencies. Facebook paid a $550 Million settlement related to their facial recognition technology. What is going on?

These companies are reacting wisely to the potential for bias and the potential abuse of this technology in law enforcement. Let’s examine three main issues related to the use of facial recognition technology in law enforcement: bias, lack of federal regulations, and too many regulations at the local level.


Is this software biased? Almost certainly, but…

Glenn Gow

Board Member | CEO Coach | Advisor | Guiding companies through technology disruptions | Helping companies grow faster

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