Technology runs the world. If you want to change the world, learn to code.
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Last Updated on December 18, 2020
Technology has taken a vantage leap in providing solutions for man. Before now, technology used to appear complex and would require a great deal of expertise to handle solutions available. Today, we have technology applicable in the simplest human activities as smart products with intelligent algorithms powering them as they make error-free judgments and provide intelligent and analytic solutions.
This article from Credit Suisse, tells us that technology does not have all the answers because it has been found to exhibit “similar biases,” as humans. No one can discredit the impact of technology, but it is not totally free of human input and this is the reason we experience these biases in many areas we have technology holding foot.
This article suggests that the process of creating technological solutions be made transparent and subject to contribution from many people who would end up as users of the product – male, female, young, old, learned, unlearned and all other preferences as we have them. It also underscores the importance of having women on product development teams. This approach is not sure to eliminate all forms of bias, but it is a good way to start in order to appraise the full benefits of technology.
Technology so far has been a major connecting tool amongst us humans. It is used and appreciated by all regardless of race, language and sex. In order to keep it less subjective to these arguments about human biases. I believe we should gather opinions on products and solutions before making them available to the public. This could be done by gathering input from intended target users and receiving feedback across the stages of production.
“Recognizing the problem is a start…success will depend on inclusive technologies that meet this vast untapped market.” This cannot be more apt especially at a time when we look up to technology for solutions. We should not muzzle our progress with technology by battling algorithm bias. The first way to avoid this battle is by reading this article here.
