Can technology affect human morality? This is not an esoteric test question from a college philosophy class, but a real, growing concern among leading technologists and thinkers. Technologies like social media, smartphones, and artificial intelligence can create moral issues at scale, and technology experts specifically and society generally are struggling to navigate these issues. On the one hand, technology can empower us with better information on the consequences of our actions, as when we use the Internet to research how to reduce our environmental footprint. In the past, such information may have been inaccessible or impossible to source, but today we can easily arm ourselves with data that helps us make choices we perceive to be more moral.

In this special guest feature, Saranyan Vigraham, Vice President of Engineering at Petuum, believes that as technology creators, we have an inherent bias in solving challenging technical problems. For democratizing AI, it is also important to solve problems around adoption and the last-mile problem of AI delivery. In a manner similar to e-commerce, an entire ecosystem of players will emerge to tackle this challenge down the road. Previously, Saranyan was a VP of engineering at Elementum, where he led their enterprise SaaS platform team that digitized the supply chain for Fortune 500 companies like Starbucks and Johnson & Johnson. Prior to Elementum, he was the head of software engineering at Meta, delivering the industry's first Augmented Reality platform with natural gesture controls.

For Intel, Microsoft, Hewlett-Packard, and the like, Computex in Taipei this week is the Oscars of the information technology world. There is the flurry of product hype, from virtual reality (VR) headsets to the internet of things (IoT) to artificial intelligence (AI) devices. One big topic that everyone has in mind is: machine learning. The idea of a thinking machine goes back at least as far as 1950, when British computer scientist Alan Turing famously wrote that if a machine was indistinguishable from a human during text-based conversations, then it was "thinking." Naturally, big tech giants such as Google, Facebook, and IBM, have all set up corporate labs to advance machine learning.