The rocket ship trajectory of a startup is well known: Get an idea, build a team and slap together a minimum viable product (MVP) that you can get in front of users. However, today's startups need to reconsider the MVP model as artificial intelligence (AI) and machine learning (ML) become ubiquitous in tech products and the market grows increasingly conscious of the ethical implications of AI augmenting or replacing humans in the decision-making process. An MVP allows you to collect critical feedback from your target market that then informs the minimum development required to launch a product -- creating a powerful feedback loop that drives today's customer-led business. This lean, agile model has been extremely successful over the past two decades -- launching thousands of successful startups, some of which have grown into billion-dollar companies. From facial recognition technology that has a bias against people of color to credit-lending algorithms that discriminate against women, the past several years have seen multiple AI- or ML-powered products killed off because of ethical dilemmas that crop up downstream after millions of dollars have been funneled into their development and marketing.

As more companies adopt AI, the risks posed by AI are becoming clearer to business leaders. That is driving many companies to hire AI ethicists to help guide them through an ethical minefield. But just as data scientists proved to be as elusive as unicorns, qualified AI ethics are also in very short supply, says Beena Ammanath, executive director of Deloitte's AI Institute. "We've seen different models evolving. It's still very nascent," Ammanath tells Datanami.

As more companies adopt AI, the risks posed by AI are becoming clearer to business leaders. That is driving many companies to hire AI ethicists to help guide them through an ethical minefield. But just as data scientists proved to be as elusive as unicorns, qualified AI ethics are also in very short supply, says Beena Ammanath, executive director of Deloitte's AI Institute. "We've seen different models evolving. It's still very nascent," Ammanath tells Datanami.

As more companies adopt AI, the risks posed by AI are becoming clearer to business leaders. That is driving many companies to hire AI ethicists to help guide them through an ethical minefield. But just as data scientists proved to be as elusive as unicorns, qualified AI ethics are also in very short supply, says Beena Ammanath, executive director of Deloitte's AI Institute. "We've seen different models evolving. It's still very nascent," Ammanath tells Datanami.

"Never before in history have such a small number of designers – a handful of young, mostly male engineers, living in the Bay Area of California, working at a handful of tech companies – had such a large influence on two billion people's thoughts and choices." Those are the words of Tristan Harris, former design ethicist at Google and founder of Time Well Spent, a not-for-profit initiative to help educate businesses, users, and designers about morally acceptable technology design choices. However, he and the entire high-tech industry may not be going far enough, or fast enough. Take for instance Google, Tristan's former employer. Recently at their annual I/O conference, Google CEO Sundar Pichai demonstrated the company's "Duplex" technology nested within the Google Assistant project.