Originally published August 18, 2017
Here is an excerpt:
Humans possess inherent social, economic and cultural biases. It’s unfortunately core to social fabrics around the world. Therefore, AI offers a chance for the business community to eliminate such biases from their global operations.
The onus is on the tech community to build technology that utilizes data from relevant, trusted sources to embrace a diversity of culture, knowledge, opinions, skills and interactions.
Indeed, AI operating in the business world today performs repetitive tasks well, learns on the job and even incorporates human social norms into its work. However, AI also spends a significant amount of time scouring the web and its own conversational history for additional context that will inform future interactions with human counterparts.
This prevalence of well-trodden data sets and partial information on the internet presents a challenge and an opportunity for AI developers. When built with responsible business and social practices in mind, AI technology has the potential to consistently – and ethically – deliver products and services to people who need them. And do so without the omnipresent human threat of bias.
Ultimately, we need to create innately diverse AI. As an industry-focused tech community, we must develop effective mechanisms to filter out biases, as well as any negative sentiment in the data that AI learns from to ensure the technology does not perpetuate stereotypes. Unless we build AI using diverse teams, datasets and design, we risk repeating the fundamental inequality of previous industrial revolutions.
The article is here.