5/5 (1)

As I’m writing this blog post, both Solar Team Delft and Solar Team Eindhoven are leading their class in the World Solar Challenge 2017. Dutch students winning prices with solar-powered vehicles isn’t something new or remarkable. However, Dutch former students presenting a fully solar-powered car that is suitable for the public roads definitely is.

Lightyear is a Dutch company, originated from Solar Team Eindhoven, and will launch their first marketable car in 2019. The Lightyear One, as the model is called, should be able to drive for a promising 800 kilometres with a fully charged battery. Which can be done via the ‘traditional’ charging plug or through sun light. As for Dutch weather conditions, the car should able to cover a distance of around 10.000 kilometres solely on solar energy. With the right sunny conditions (e.g. Hawaii), the Lightyear could potentially drive for months at a time between charges.

Does this mean Elon Musk is losing sleep over this new form of sustainable driving?

Probably not, because Lightyear is just the latest challenger to Tesla’s number one spot in the sustainable automotive market. However, if the claims made about the groundbreaking technological potential are true, this may indeed be the new disruption in the car industry. Nowadays, for example, electric cars are being restricted to the areas with reliable charging networks.

Lighyear believes the real future of automotive power will be fully powered by the sun. In 2015, the Solar Team Eindhoven already won the Crunchies for best technological achievement with their solar car “Stella”, beating Apple, Bitcoin and Elon Musk’s SpaceX. So, the technical minds behind the car aren’t new to the solar scene. The main downside to the company, as you probably already expected, is that it comes with quite a price tag: €119.000.

Lightyear still has to prove it can transfer its experimental en potential tech solutions into a fully realized consumer experience. Nevertheless, I believe that solar powered vehicles, The Lightyear One or any other type, will be the next disruptive step in the automotive future.

Nederlanders brengen eigen zonne-auto op de markt. (2017, 29 juni). Geraadpleegd op 10 oktober 2017, van https://nos.nl/artikel/2180593-nederlanders-brengen-eigen-zonne-auto-op-de-markt.html

Rijden op zonne-energie: Lightyear One. (2017, 30 juni). Geraadpleegd op 10 oktober 2017, van https://www.nu.nl/auto/4804164/rijden-zonne-energie-lightyear-one.html

Etherington, D. (2015, 5 februari). Stella’s Solar Car Wins The Crunchie For Best Technology Achievement. Geraadpleegd op 10 oktober 2017, van https://techcrunch.com/2015/02/05/stellas-solar-car-wins-the-crunchie-for-best-technology-achievement/

 

 

 

 

 

 

5/5 (2)

Don’t worry about robots; new jobs are on its way!

If you’re curious about what the rapid technological developments nowadays mean for the job market, you very likely came across a bunch of worrying technosceptics quoting headlines like ‘robots take over our jobs’ and ‘will doctors be replaced by Artificial Intelligence?’

The fact that those topics are becoming part of peoples daily thinking isn’t that weird though. It seems like a bold statement to argue that humans are in many aspects disabled relative to their digital counterpart, but there are quite some sound arguments in favour of it. First of all, humans are simply to slow and get easily tired. Where a computer can absorb all medical journals or case law over the last decade in just one day, humans read only one article a day on average. Until recently, computers were not able to understand those articles on the same level as humans did. However, the IBM’s Watson Supercomputer beating all it’s human opponents on Jeopardy was the first convincing exhibition proving otherwise.

Our second disability is that we’re only able to see relatively simple patterns. Algorithms, on the other hand, have the superior ability to analyse complex patterns. This was clearly illustrated by Google’s Deepmind AlphaGO, beating the game’s world champion last year. More practical examples are researchers from Stanford that are able to automatically recognize skin diseases with the latest AI-technologies, beating all of its dermatologist opponents in almost every test. Or the Google research report, where they detected cancer trough deep learning mechanisms at the Radboud Medical Center, outperforming pathologists with a 16% higher average accuracy.

But what does this mean for our future jobs? Will humans become redundant indeed? In order to be able to make an ‘educated guess’, we have to use something machines don’t posses: our imagination. Imagine you were an American farmer in the year 1900 and someone from the future (around 100 years later) came along to tell you that instead of 40% of the population, only 2% of the people were farm employees and there wouldn’t be food shortage. And if you then would’ve had to guess what the other 38% were doing, you probably would not have said IT-consultant, truck driver, social media influencer or hacker. The same goes for us nowadays, we don’t know what the job market is going to look like when robots and artificial intelligence really take over the office floors.

The Camelyon Grand Challenge 2016 also showed that pathologists that worked together with AI technology, made less mistakes in diagnosing cancer than each individually. That’s why I argue to bet on human-machine interaction. If we’re able to find the right synergy, we’ll have a whole different job landscape in 100 years, including vacancies for robot walkers. Why would this be bad? We would still be employed and probably work a lot more efficient. We’re only scared today because we can’t imagine the job descriptions of tomorrow.

Autor, D. (2016, September). Will automation take away all our jobs? [Video file]. Retrieved October 9, 2017, from https://www.ted.com/talks/david_autor_why_are_there_still_so_many_jobs#t-1044890

Computer kan kanker beter herkennen dan patholoog. (2017, March 3). Retrieved October 9, 2017, from https://nos.nl/artikel/2161091-computer-kan-kanker-beter-herkennen-dan-patholoog.html

Stumpe, M., & Peng, L. (2017, March 3). [Assisting Pathologists in Detecting Cancer with Deep Learning] [Blog post]. Retrieved October 9, 2017, from https://research.googleblog.com/2017/03/assisting-pathologists-in-detecting.html

Welling, M. (2017, February 25). De AI-dokter. Retrieved October 9, 2017, from https://fd.nl/morgen/1188887/de-ai-dokter