Economies of the Future: Disruptive Technology, the Myth of Capitalism, and Why Ordinary People Don’t Get Wealthy

a Tech 2025 Think Tank and live podcast recording

Featured Speakers: Denise Hearn, co-author of “The Myth of Capitalism: Monopolies and the Death of Competition” and Live Recording of “The Local Maximum” podcast with host Max Sklar

Think Tank Discussion  

Join us for our next think tank discussion. Our think tanks are interactive, open discussions, and an exchange of information and ideas between our expert guest speaker(s) and the audience — everyone gets the opportunity to share their opinions and ideas. We encourage and facilitate thought-provoking, respectful discourse as we all struggle to understand sweeping changes that are coming to our world!

The Topic:

The anger in Northern California and elsewhere in the United States springs from an increasingly obvious reality: the rich are getting richer while many other people are struggling. It’s hard not to wonder whether Silicon Valley, rather than just exemplifying this growing inequality, is actually contributing to it… Does the region really portend a future… in which a few very rich people leave the rest of us hopelessly behind?” — David Rotman (Technology Review)

Jason Calacanis (a serial technology entrepreneur and arguably one of the most successful and respected angel investors in Silicon Valley) knows why you’re not wealthy. In a recent blog post, Why People Don’t Get Wealthy, Calacanis listed nine reasons why people don’t get wealthy:

Guest Speaker: Denise Hearn

1. A lack of skills
2. Lack of taking risks
3. Not building a network
4. Poor work ethic
5. Not reading books
6. Giving up after getting beat down
7. Fear
8. Being born at the wrong time
9. Being born in the wrong country

After tweeting his blog post where he also laments the growing trend among young people to embrace socialism over capitalism, a lively debate ensued with people tweeting their reasons for why people don’t get wealthy and whether capitalism has failed.

What does disruptive, emerging technology have to do with the inability of people to “get wealthy?” Apparently, a lot. One of the largest and most prominent debates in social sciences and economics today is the role of technology in inequality.

“But the biggest factor of why technological changes can contribute to inequality, Brynjolfsson says, is that the technology-driven economy greatly favors a small group of successful individuals by amplifying their talent and luck, and dramatically increasing their rewards. Brynjolfsson argues that these people are benefiting from a winner-take-all effect originally described by Sherwin Rosen in a 1981 paper called “The Economics of Superstars.”” — David Rottman (Technology Review)

According to McKinsey Global Institute’s recent report on the Impact of AI on the world economy, Artificial Intelligence has the potential to incrementally add 16 percent, or around $13 trillion, to current global economic output by 2030. How will this new wealth be distributed? What new economic systems will come out of this? Who will benefit from this new wealth, who will lose, and who will simply disappear?

In this think tank, we will tackle these questions and the question posed by Jason Calacanis with guest speaker and author, Denise Hearn, who will provide much-needed perspective on what’s really happening and the root causes of our economic instability and widening income gap as a result of technological disruptions (among other factors). Max and his production team will do a live episode recording of their show, The Local Maximum Podcast, including getting certain audience feedback, and will interview Denise Hearn.


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Denise Hearn

Denise Hearn writes, presents, and consults on economic justice and systems change aimed at human flourishing. She is co-author of The Myth of Capitalism: Monopolies and the Death of Competition – named one of the Financial Times’ Best Books of 2018 and endorsed by two Nobel Prize winners. Denise has presented to over 50,000 people at venues including: the Oxford Union, Bloomberg, a Canadian Parliamentary Standing Committee, and group homes for foster children. Most recently, Denise was Head of Business Development at Variant Perception – a global macroeconomic research and investment strategy firm that caters to hedge funds and family offices. She has also built new impact investment models in Canada, helped create the world’s first Trustmark for Sharing Economy companies in the UK, and was chosen for the Alt/Now: Economic Inequality residency program at the Banff Centre in 2016.

Max Sklar

Machine Learning Engineer and Host of “The Local Maximum”

Max Sklar is a machine learning engineer at Foursquare. He focuses on using machine learning and heuristics to develop new features and products. More recently he has led the development effort of the Marsbot app, a bot that texts local recommendations, and on a new methodology for Ad Attribution – a step forward for the industry.

His specialties include: Google Maps, Algorithmic Design, Automated Theorem Proving, Agile Practices, Functional Programming, User Interface Design, Object Oriented Design, Database Fundamentals, Web Application Development, Usability Analysis, Search Engine Design, Product Requirements, Java, Javascript and AJAX, C++, PHP, Several SQL Dialects, Python

Max has spoken at a variety of conferences and universities, including the ACM conference on Recommender Systems, the Cambridge Workshop on Urban Data Science, and Talkabot 2016.


Expanding our perspective about technology and the future.

Hosted by Max Sklar (former Machine Learning Engineer at Foursquare, currently at Luminary Media), The Local Maximum Podcast is a weekly podcast, launched in 2017. The phrase “Local Maximum” is a mathematical term, and it refers to a point at which you need to step down in order to reach new heights. But people – not just points – can get caught in a local maximum. That means they’ve gone as far as they can through one strategy which has gone stale and they need to search for new ideas.

In product design and machine learning, we sometimes ask if we’re in a local maximum, and whether starting from a fresh perspective can lead to better results.

So this podcast is about examining technology, engineering, and social trends through the lens of expanding perspectives and moving beyond the Local Maximum both for ourselves AND for our algorithms. Max and his guests explore techniques to understanding the world of AI and Machine Learning that an average person can understand – and he shows how to get our algorithms to be more flexible through the same process we use on people. Listen to Max interview Charlie Oliver (CEO of Tech 2025) on The Local Maximum HERE.


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