Microsoft MSFT and Israel-based startup AnyVision — which offers facial recognition-based offerings — recently issued a joint statement.
The report states that the tech giant will divest its stake in AnyVision as well as stop making minority investments in other companies that offer facial recognition technology.
Microsoft has been extra cautious on use of facial recognition technology, which it asserts to be undertaken in a transparent manner, not impeding any individual’s fundamental right to privacy.
The withdrawal of investing in companies that primarily provide sensitive technologies including, the controversial facial recognition technology, is expected to boost the company’s brand reputation and instill investors’ optimism in the stock. Microsoft currently carries a Zacks Rank #2 (Buy).
Notably, shares of the company have returned 25.8% in the past year outperforming the industry’s rise of 8.5%.
You can see the complete list of today’s Zacks #1 Rank (Strong Buy) stocks here.
Into the Headlines
Per Crunchbase data, AnyVision raised around $74 million in funding. Notably, M12, the venture capital arm of Microsoft, has had been a comparatively new investor in the startup.
In 2019, Microsoft fell under the scanner for having invested in the startup, which per media reports, was using facial recognition technology to “surveil Palestinian residents in the occupied West Bank region.”
The recent audit of the investigation states that AnyVision’s technology has not been used in the alleged mass surveillance program.
Financial term of the divestment and the timeline is not yet divulged. Moreover, it is unclear whether other M12 stakes will be affected by the change in the investment strategy.
Key Takeaways: Unbiased AI & Ethical Use of Tech
Facial recognition technology is increasingly being leveraged by various public and private companies, government agencies, among others, to fulfill their respective requirements. The use of the tech is almost infinite, for instance, unlocking screens, identifying and uniting family members, receiving suggestions for tagging a person on a picture, to mention a few.
The improvements in sensors and cameras, and strengthened machine learning (“ML”) capabilities are paving the way for companies and government agencies to increasingly leverage facial recognition technology. Per MarketsandMarkets data, the global facial recognition market is envisioned to grow at a CAGR of 16.6% to $7 billion by 2024 from $3.2 billion in 2019.
Nevertheless, bias in AI has been doing the rounds for quite some time now, which is why the use of facial recognition tech has been controversial. The companies, especially the tech behemoths are aiming to minimize errors relating to biased outcomes.
Notably, Microsoft rejected a few facial recognition-focused deals on violation of human rights. The tech giant aims to develop facial recognition software for commercial and public sector use in an ethical manner.
In July 2018, Microsoft president, Brad Smith had voiced his concern over the ongoing use, misuse, abuse and overuse of facial recognition technology, via a blog post. Smith had necessitated the need to go slow on the use of facial recognition technology in a bid to be socially responsible.
The company has had asserted for regulation of a few aspects of the technology to protect the very basic ideas of freedom and privacy. To start off, approval of the people coming under the scanner are often not considered. Microsoft remains highly concerned with this violation of a fundamental right, which has been going on for quite a while.
The next significant issue is the credibility of the technology. Facial recognition technology accompanies a considerable bias in the way it functions. Notably, various studies have proven that the technology is surprisingly erroneous.
Major tech giants, including International Business Machines Corp. IBM, Alphabet GOOGL, Facebook FB, are focusing on enhancing their respective offerings with focus on unbiased AI, and improving credibility in terms of data use. Facial recognition technology is an important aspect in the broader unbiased AI space.
The focal point is to tame and train the algorithms accordingly. Improving ML capabilities on a dynamic basis will aid the process.
Government regulations, transparency and accountability of the entities leveraging facial recognition technology is anticipated to make the transition from biased to unbiased AI smoother. Reducing bias component is expected to be a key catalyst, going forward.
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