Machine Commons Podcast, the profound impact of machine learning.

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Ok, not the most succinct title. After fielding a few ideas ("Keeping AI on things", "Me, myself and AIrene", "Not so bad robot",...), we decided we should just call it what it is. And it is the Machine Commons Podcast, where we interview guests about the profound impact of machine learning.  

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Welcome to our podcast, where we explore the various and far reaching impacts of machine learning - the software approach better known as artificial intelligence (or, AI).

The world has teetered over an invisible edge, where more of our lives are governed by software that is decreasingly coded and increasingly trained - a world where our governing software 'learns'.

It is the technology at the cross section of multiple advanced fields.
Come hang out with Alex and Lucie, as they ask the smart and the dumb questions about this profound technology.

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Series 1: Social Good

For our launch season, we couldn't be more proud of our partner 'Omdena'.

Omdena is a global organisation that channels the work of expert and aspiring data scientists to solve real world social issues with artificial intelligence.

Episode

5

1/1

The world *needs* artificial intelligence

Sijuade Oguntayo is an AI professional in Nigeria, donating his time to local community initiatives alongside his regular AI projects and passion for computer vision. Food security is a major concern and he tells us how he trained AI to shoot lasers (Skynet anyone? Nervous collar tug). His breadth of experience is fascinating, his broad enthusiasms reflecting the varied potential of AI applications across government and all industries. His mind is as broad, with personal philosophies extending across multiple fields. The interview culminates in commentary about the future, the growing importance of intelligence, a conversation with 'Jarvis' (AGI) and how the world needs AI to survive. Get the popcorn.

Episode

4

1/1

Privacy is a 'WE' thing

Albert Yumol is an activist who exposes corruption with data science. He teaches Filipinos - literally door knocking at times - about the importance of data privacy. This task is made mildly more difficult by the fact that people in the Phillipines don't really have the concept of 'self'. His mitigation: that privacy is in fact a 'we' thing (not an 'I' thing). As much a fascinating discovery of his homeland archipelago, he emphasises the importance of basic data quality before you can even get to the clever stuff - although he also shares some clever stuff. His enthusiasm is endless.

Episode

3

1/1

The robots are taking over - robotic process automation

Chris and Henk lead GRN - a robotic process automation consultancy. At the heart of every business is people. Every person's workday is comprised of processes. How many of these processes can be automated? What happens to the people when they are? Our conversation climaxes when discussing the intersection of machine learning and RPA: what happens to society when we train code that programs automations, which generates more data to train code, to create automations, to train code… Our future depends on one thing: our ability to remain in control.

Episode

2

1/1

AI, Ethics and Capitalism - tools are just tools

Tony Tong is a risk taker because it's less risky to take risk. He's a Google Explore machine learning facilitator, a software engineer at Rakuten Asia and volunteer at Omdena. He's a capitalist at heart but with an eye for social good. He argues data science is simply a tool and that 'good' comes down to intent. We begin by talking about life in 2021 - what it is like to 'live with algorithms', and we finish on the idea of 'move fast and break things' and the future of machine learning.

Episode

1

1/1

The human problem with artificial intelligence

Marijn Markus, artificial intelligence leader at Capgemini Netherlands - a major management consultancy, talks us through the human problems in AI. We explore bias, the cruciality of diverse teams, the need to put agendas on the table, the insanity of innovation KPIs, the mutual exclusivity of privacy versus transparency, and the general inevitability of the data-fuelled artificial intelligence revolution.