Today technology is inextricably entwined with just about every activity that humans undertake. Techonomy embraces that fact, and seeks as a company to help the world take advantage of it. We cast our lens broadly across business and society in order to highlight and explore the manifold ways in which tech's impact is felt. Techonomy Media hosts conferences and dinners and publishes editorial content, including video journalism. We make our programs accessible to a wide audience because it is impossible to know where leaders will emerge, and because the world increasingly recognizes that, for better or worse, we are all in this together.

From Elon Musk to Mark Zuckerberg, the titans of tech today have more notoriety than movie stars of yore and, often, the egos to match. But at what point does idolatry--within the culture of tech and beyond it--and internal self-regard get in the way of progress rather than bolster it? This was the subject of Techonomy founder David Kirkpatrick's conversation with Autodesk CEO Andrew Anagnost at Techonomy 22, which took place November 13-15 at the Fairmont Sonoma Mission Inn & Spa. Within moments of welcoming Anagnost to the stage, Kirkpatrick dove right in. "Do you think tech has an ego problem?" "I do," replied Anagnost, who used the phrase "celebrity technologist" to characterize leaders known as much for their personalities as innovations--and who may prioritize image over achievements.

We've reached a point "where AI and machine learning are converging" and it's helping drive operational efficiencies and customer experience (CX) innovation for a wide range of businesses. That's how author and veteran IT expert Tom Davenport began a wide-ranging discussion about the state of AI and automation in the financial services sector at a recent virtual salon with senior industry executives. Another speaker, Rob Krugman, Chief Digital Officer at financial services firm Broadridge, said his firm is "increasingly using AI models to define and select the attributes and information that is important to their customers". The session was hosted by Bill Wright, Head of AI Machine Learning and Edge Innovation for Red Hat. It was moderated by CDX.

If the pandemic has taught the world anything, it's that we are capable of moving much, much faster to make change. By one measure, 42 percent of the workforce in America alone was working from home in June. Now, as we seek to combat COVID-19, 155 vaccines are in development, including 10 vaccines undergoing phase 3 trials; many of these teams are already achieving encouraging results in remarkably short order. Several 1,000-bed hospitals were built in China in just over a week. Doctors are seeing 50 to 175 times the number of patients via telemedicine as they did pre-COVID.

"This is a human problem," said Vivienne Ming, a longtime computer scientist and entrepreneur who calls herself a "professional mad scientist." She was talking about the problem of keeping artificial intelligence ethical. Software that learns or evolves over time while doing tasks–a rough definition of this complex category of technology–is poised to play a greater and greater role in modern society. Techonomy recently brought together a trio of leaders and technologists who are excited by its potential but committed to doing so carefully for a Tech session. These experts all agree that thus far, AI hasn't fulfilled its promise, because it hasn't been designed with sufficient ethical intention. In addition to Ming, we heard from leaders of two major companies that take AI ethics seriously–software giant Salesforce, represented by Paula Goldman, chief ethical and human use officer, and global technology services firm Wipro.

The Tally robot, from Simbe Robotics, helps out in stores so people can be freed from the monotonous task of checking shelves for inventory. Wouldn't it be nice if robots could clean our office, greet clients or put away the groceries at home? But even though we want and often embrace advances that make our lives simpler, the vision of robot as dutiful helper hasn't come to fruition. Robotics has made a big difference in manufacturing, but has failed to make it into our homes and businesses in a meaningful way. It turns out the challenges are plentiful.

One of the problems of the Second Artificial Intelligence (AI) Winter (1987-1993) was that there was not enough data to go around. We did not yet understand the value of "Big Data," and academia was working on models fueled by "Small Data." However, now we have entered the era of "Bigger Data Than We Ever Imagined." We are producing data on the order of exabytes. It is predicted that by 2020 we will use zettabytes.

The other night I attended a dinner with a dozen CEOs of AI startups. Once again, I heard a near universal discomfort with the term "artificial intelligence" as they sipped Pinot Noir and fumbled to describe what they do. "We're not really trying to create intelligence that's artificial," said the CEO of a product strategy company. Another, who has built AI-based payment technologies, found the term dystopic. "Too many people think AI means the Terminator," he said.

Imaging and understanding the brain is getting so good we are on the cusp of truly enhancing it. This article originally appeared on SOSV.) As I start to look at the emerging trends of 2017 from the vantage of IndieBio, where we see hundreds of biotech startup applications and technologies per year, a few key themes are already emerging. Even as political landscapes change, science and technology continue to push forward. Most of us have seen science fiction shows that show future doctors regrowing and replacing entire organs.

Interesting write-up by Jennifer L. Schenker published end of January on Techonomy. "We should not let Silicon Valley be the mission control for humanity," argues futurist Gerd Leonhard, author of a new book called Tech versus Humanity: The coming clash between man and machine. If autonomous AI software, crunching data far more rapidly than humans, can help eradicate disease and poverty and introduce societal improvements and efficiencies, then we must embrace it, Leonhard says. But "at the same time we have to have governance. And right now there is no such thing."