Neuroplasticity, data as an economy, an alternative to displacement and a toolbox of technologies.
Pearls of wisdom from the AIIA podcast Episodes 41-45Add bookmark
For this instillation of AIIA Podcast key takeaways- we discover neuroplasticity, data as an economy, an alternative to displacement and a toolbox of technologies.
Episode 41 Yuval, Dvir, Google
When we hire someone for the job, we want 30 years of experience in the specific field. They can be good, but that doesn't really bode well for neuroplasticity.”
This comment is loaded with information. First, executives with artificial intelligence experience are extremely hard to find. And there is zero corporate talent with three decades of enterprise AI experience. Second, while there is a tremendous amount of industry handwringing on that issue- Yuval is saying it’s ok. You don’t innovate using yesterday’s design. Neuroplasticity is the ability for the brain to change, which all carbon-based intelligence will need in this fourth industrial revolution. Third- and maybe this one should go without saying-your artificial intelligence also needs consistent change.
Episode 42 Tyrone Grandison, Eisenhower Fellow
You're signing everything away. I mean, you're also giving a lot of control over to companies that use the data that's generated about you and the data you enter about yourself as their intellectual property, as their assets.
This comment may still be ahead of its time. But as we make our way more fully into 2019 in search of business models in the industrial revolution- one wonders how long personal data can be ignored as an actual currency. Funnel it through blockchain technology and you’ve got the makings of a truly disruptive model.
Episode 43 Richard Frost, Yorkshire Building Society
"Is your integration partner a match for us; are they ten times our size and then they will just walk all over us? When we want to start working with them, will they send in the B team once the sale has been made? And then finally, does their functionality fit our functionality?"
These key questions continue to seemingly and surprisingly be ignored. There remain consistent examples of the wrong integration partner working with the wrong corporate enterprise to the tune of especially terrible results. Meaning, these are integration partners who have success elsewhere and these are enterprises who have success implementing other technology. This is another great example of how the old tried and true methodologies behind good business need to be employed for AI & Intelligent Automation…and must not be ignored to ‘save time to gain quick wins.’
Ep.44: Camilla Kwong, Close Brothers
“Things change, the market constantly demands more, your end-customer demands more, so I think it's pretty shortsighted to say everybody's job's going to get replaced by robots. We are creating new skills. We're serving the customer better.”
It seems that Camilla is talking about the fact that re-hiring for the same cut-and-paste position isn’t happening. Up-skilling is happening. And the sheer volume of new positions that will be filled in the next five years is vast. Just ask the social media influencer campaign manager who has a communications degree.
Ep.45 Ep.45: Martin Ruane, Engie
"One of the things I've put forward is a different operating model of we might operate in the future not just based on RPA, which is a component part, but based on AI to digitize our interface. Based on analytics to analyze the data based on the sensors, based on augmented reality. Based on a range of technologies that actually allows us to make sure the value is where it's created, which for us is when people go out and maintain things and fix things. But try and move that to more of a proactive maintenance side rather than a reactive maintenance side."
And so, Martin is looking to advance the current business model by blending technologies. He’s looking to ensure that the enterprise of today is a digitally transformed enterprise of tomorrow. He’s not letting a technology lead him. He’s looking at a tool box full of technologies and finding the right ones at the right time at the right cadence to deliver a different and better experience in the future.