Trying Too Hard
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“While the podcast is slick and sounds professional it kind of loses sight of its topic, technology, and the credibility of the type of school it is. I’ve listened to 6, and enjoyed the first 2 that were mostly informative and interesting, then podcast quickly started skewing towards opinions, a narrative, and political. The interview on the woman from Google I had to skip after about 14 minutes of learning absolutely nothing other than a simple explanation of why this woman got fired, which is she whines non-stop, is a narcissist, entitled, somehow thinking she’s qualified to manage a team at a young age and with not much work experience, thinks she knows more than everyone else who is much more experienced than her, and wastes company time with her bosses always having to answer her, and ineffective use. People hire friends because they need to know they’re qualified and their work ethic so they don’t end up hiring people like this woman who look good on paper but are not a good employee. Spending days with a staff investigating 100s of resumes costs the company money and is a complete waste of resources. She works in AI at an AI company, and there are many better ways of going about it, yet she insists her way is right and others are dumb for not implementing it? I was embarrassed for her. This is literally the worst interview I’ve ever heard, an embarrassment for women, and I can’t believe MIT posted it. It’s literally damaging for women. And there are interviews from FB and Twitter on misinformation? They are literally responsible for spreading it while making billions off of spreading it, so why are they being interviewed to essentially point the finger? FB profits from phishing schemes even. I know ‘cause I accidentally clicked on one, and I’m convinced FB is responsible for why everyone gets scam calls now. And Twitter sets up its algorithm to manipulate what it wants you to see. I experimented with it. Not to mention, they’re not at all responsible for monitoring what goes on there, despite what they claim. Overall, stick to the technology. I found from a journalistic point of view the content fairly weak, and coming from young and inexperienced writers who haven’t lived long enough to have a full view of how things work. And, simply, the information was wrong in some places, aside from a negative, semi-apocalyptic view of things. Cameras are put outside of drug stores where there is crime, not based on skin tone. l’ve lived in both a poor, working class, high crime area where they went up, and an affluent area where they went up after a slew of crimes happened. From a science perspective, the minute you have a bias the science is contaminated, which is exactly what this podcast does. Good journalism is giving the information and letting the audience decide for itself. The podcast literally convinced the public tech and AI is bad...which isn’t good for a school that charges high tuition to teach those exact subjects. I’m on the fence whether I will continue listening. Informative, but too dark and opinionated, and a bit naive.”
Plasticanimalz via Apple Podcasts ·
United States of America ·
03/02/21
More reviews of In Machines We Trust
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“Great podcast”
Diana from Northbrook via Apple Podcasts ·
United States of America ·
08/13/20
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“I thought this episode was excellent! I really enjoyed the information about how prices are set! It gives a completely different view of supply and demand! Keep up the good work! Loved it!”
Mrs spg via Apple Podcasts ·
United States of America ·
10/27/21
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“The authors make scientific, AI related talks easy to understand for public and interesting at the same time. There is Something new to learn in every episode for me. It would be good if you consider to cover some topics requested by the audience, most wanted for current situation with remote...”Read full review »
Nata_Pri via Apple Podcasts ·
United States of America ·
10/01/20
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