If by 2050, 70% of the world’s population will be living in cities - how do we reimagine our infrastructure, resources and services to cope? Bala Mahavaden is one of the thought leaders involved in planning the next generation of super cities in India, the Middle East and Europe. We spoke about the role of data in tomorrow’s cities, digital identity and citizen information, and how predictive analytics might help civic leaders mitigate day-to-day problems and response to crisis.
Futurist Mike Walsh discusses the relationship between automation and employment, and why, if the previous Industrial Revolution is any guide - we should be cautious in assuming that robots will be the end of jobs as we know it.
It would be easy to imagine in this age of Teslas, Powerwalls, and Nest thermostats, that we are somehow on the brink of escaping traditional energy sources forever. Yet, oil, gas and coal persist - and continues to shape economies, nations and industrial policy. Dr. Kent Moors, a global expert on energy and a professor in the Graduate Center for Social and Public Policy at Duquesne University, where he directs the Energy Policy Research Group, has some ideas on why that may be. He has also had a fascinating life. You will hear how I try, unsuccessfully on a number of occasions, to get him to talk about his former life as a covert operative working for the State Department.
I had to learn this one the hard way, but luckily my singing teacher taught me this little trick to remove the frustration out of my voice!
A few years ago I had a morning keynote in Orlando and a keynote the next day in St. Thomas, VI. Flights were confirmed, I’d be in early the night before, no problem.
Or so I thought.
A one hour rain delay in Orlando caused me to miss the St Thomas connection and the backup had been canceled. There were no flights that would get me into St Thomas in time for the keynote the next morning.
I mean no flights.
First, I was immediately in contact with my client’s meeting professional, keeping her apprised of the status as it unfolded. For hours I was talking to airlines in person, on the phone with my agent, on the phone with my office manager, scouring the earth for transportation options. We tried every airline, every routing… New York, Newark, Puerto Rico… even ships: there was no way. I couldn’t find a good-enough replacement speaker on short notice close enough to get there. I was the closing speaker so they couldn’t just bump my show back. I was the only outside speaker I had tobe there. We even checked chartering a jet. At first they said $15,000 - that’s crazy. Then, once they realized my desperation, instead of helping they gouged the price up to $17,500, more than twice what I was making on the show for my fee at the time, and I was definitely no millionaire. Forget that.
The whole time I’m remembering my own keynote advice…
What if I could? I know it’s impossible, but what if it wasn’t, what would I do?
So what would you do? Would you…
- Flyi in late and hope enough people can stick around?
- Fly home knowing it’s totally not your fault, you did your best?
- Pay the price gouged $17,500, do the performance, and lose not only your fee but costing your fee on top of that?
- Pay for a speaker out of your own pocket who’s reallynot as good but can fill the slot?
- Offer your client not one but two free makeup performances at the date of their choosing?
OK, what did I do?
- After confirming with my wife (we make all big financial decisions together), we bit the bullet and chartered the jet at $17,500.
Making the show is always, always the most important thing.
I made the show just in time, the audience loved it, and my client was extremely happy.
What I bought, though, was proof positive that I will do literally whatever it takes to be there.
You may expect the best from me every time.
One of the hardest things for any algorithmic leader is knowing when do nothing at all. This is not an entirely new dilemma. Test pilots in the early days of the space program, struggled with the idea of not having manual controls - even when their own interventions led to deadly mistakes. So just when do humans make good decisions? To get to the bottom of that, I chatted with Jason Collins, a behavioral economist, who has written extensively on these ideas at the Behavioral Scientist, and currently runs the data science team at a major financial regulator. He previously co-led PwC Australia's behavioral economics practice.
Vinh Giang is now offering a night of close-up magic before your event! Watch below for more info: