Autonomous Vehicles and Strategic Choices


This Recent Article is the result of a collaborative effort between TCS and the Clayton Christensen Institute.  The article examines the strategic choices faced by various players in the emerging Mobility Ecosystem – viewed through the lens of the Theory of Disruptive Innovation. It outlines the best course of action for achieving long-term profitability in the ride-hailing market.

As with any future scenario, the variables that must be considered in determining the path of the scenario can be overwhelming – There is Peril in Predicting. However, inaction is not an option. Strategic choices must be explored.

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The Augmented Age


Maurice Conti is the Chief Innovation Officer at Alpha focused on what he calls the Augmented Age. He talks about it this way: We’re heading for a future where our natural human capabilities are going to be radically augmented in three ways: Computational systems will help us think. Robotic systems will help us make. And a digital nervous system will connect us to the world far beyond what our natural nervous system can offer.

Car Frame

Take a look at the picture above. Can you guess what it is? It is an example of what you get when a design tool intersects with the augmented age. Take a look at the short Ted Talk below for the answer.

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The Short Term Impact of AI is Very real


I recently ran into a TCS colleague at a forum in which I presented. Ryan Metz is a Data Scientist working at our Cornell Innovation Lab. Ryan mentioned an Article he had written about the short term impact of AI – versus the long term concerns voiced by the likes of Elon Musk and Stephen Hawking. As he states in the article, the long term concern is that we will produce machines so intelligent that we lose control over them. They will become a new form of life that rules over us as we do the  the animal kingdom.

In the article, Ryan uses story telling to articulate the short term impacts of artificial intelligence – a very effective way to raise awareness. The key message: The technology that already exists, or is about to exist, is dangerous enough on its own. Ryan focuses on two artificial neural networks (algorithms modeled after a rough approximation of how groups of neurons in your brain operate): Generative Adversarial Networks (GANs) and Recurrent Neural Networks (RNNs).  A quick example of each from the article:

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Possible Futures: Exploring Deepfake and Neuralink


Two recent articles highlight the dilemma faced in this era of rapid innovation: the potential to enhance humanity, and the opportunity to diminish it. This article on DeepFakes describes the challenge that society will face as Deepfake video and audio make it impossible to tell the difference between reality and fiction. Audio attacks using convincing forgeries can send stocks plummeting or soaring. How about mimicking a CEO’s voice to request a senior financial officer to transfer money? These are real examples provided by Symantec. This short Video describes the money transfer scenario.

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The Shifting Winds of Education and Artificial Intelligence


Nick Burnett, Futurist and Education and learning entrepreneur, recently published an Article on education and artificial intelligence. The article launches a series that explores exponential technologies and their impact on learning and teaching. The post was co-authored with Nick Kairinos and the Fountech team.  A focus on learners, teachers and leaders is critical, as education is the key to success in the 21st Century.  I recommend the article.

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The Future of Cars: An Infographic


I recently came across a very good Infographic that describes the future of cars. Here is the abstract from the Carsurance website:


The future of cars undoubtedly seems exciting. Up to this point, cars were viewed primarily as a convenient method of transportation. The main advancements were made in reliability, safety, performance, and overall comfort. Carsurance InfographicHowever, the advent of the internet and artificial intelligence unlocked a whole new field of progress in the auto industry.

An automobile of the future is not just a machine for driving to your desired destination. It’s a fully automated system that makes all the decisions for you while you enjoy the latest content on its premium audio-visual system.

Want to change the route? Just give a verbal command and the cars of the future will know what to do. Worrying about crashing or getting a citation? The vehicles of tomorrow will carry self-driving software that is so reliable, humans do not even come close.

Reducing carbon emission is another crucial challenge for the car industry. Electric and hybrid cars, with their replicable batteries, seem like a convenient solution. However, future cars could rely on even more advanced fuels.

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Bias and Diversity in Computing


In the past several weeks, the topic of Digital Ethics has come up several times. A critical piece of this discussion involves the bias that is and will be built into the applications of artificial intelligence. Amy Webb is a Quantified Futurist, Professor, Strategic Foresight at NYU, and the Founder and CEO of The Future Today Institute. In March of this Year, Amy published a book titled The Big Nine.

In her book, she tackles the issues associated with bias; specifically, the lack of diversity in computing. In this recent Article, Amy discusses the consequences of computer systems that don’t anticipate all the types of people who might use them. For example, Computers have started issuing prison sentences. Bias and DiversityA quick look at one of the largest technology companies underscores the severity of the issue: At Google, more than 95 percent of technical workers are white or Asian.

In reacting to the big focus on STEM, AMY had this to say: “If everyone is focused on the nuts and bolts of making software quickly at scale, where will they learn to design it with equity and care? Critical thinking is what the computers won’t be able to do,”. I recommend both the book and the article as a means of education and awareness regarding this critical issue of bias.