Artificial Intelligence (AI) will take all of our jobs, and that’s ok
This was the initially damning sentence and also title of a Data Science breakfast meetup I attended at General Assembly this morning in Sydney. Organised by Geoff Pidcock and Anthony Tockar the roughly 50-100 people present were given a fantastic talk from Tomer Garzberg about a range of topics centered on AI and the current use of AI to replace jobs in Chinese factories simply by showing black screens of nothingness, representing that AI doesn’t and won’t need the same amenities such as running water, light and heat as us humans. That they can run in darkness, 24*7 for a period of time with little to no supervision. This is already happening!
So, unless you’ve been living under a rock and continuing your machine to destroy textile machines you’ll be aware that every day the uses of AI in employment are becoming more and more present and ubiquitous in our everyday lives and workplaces. Examples include the chinese manufactories mentioned above, AI lawyers, driverless cars as well as scores of other blue-collar work that follows a structured approach that is more easily automated.
The question you are probably asking yourself is: Is my job safe? What jobs are likely to be automated first? Well, really as Tomer and the panel this morning pointed out: No job is ultimately safe. This doesn’t mean that this kind of change will happen overnight, instead we can expect it to take generations, however, it is going to happen.
Tomer’s also spoke to a number of variables that proposed the percentage a job area would be to automated in % terms when you looked at the variance, predictability and structure of the job in question. A good example to look at for comparison is a stock taker vs animal specialist. One has a very low variance, highly predictable and structured job, the other doesn’t and the complexity of applying AI & machine learning to one is much more difficult than the other. This again doesn’t mean it can’t or won’t happen, but that it is less likely.
Related but not the same is a recent development of a data scientist that used a neural network (later posts to come to explain this) to code a basic HTML and CSS website based on a picture of a design mockup. This shows that even web development can’t escape automation 😉 Turning Design Mockups Into Code With Deep Learning
Is anybody actually ready for this change?
After the enlightening talk from Tomer this morning a panel of 4 experts in the field of Data Science & AI answered questions regarding:
- The deployment of AI in a business setting – I.e. a Junior lawyer being developed for a legal firm!
- Political & economic issues – What will the governments do when people’s jobs changes – where will they go? What is the government doing? With the current capitalist market, what regulation is required to protect those jobs that are lost and can’t be re-skilled?
- Psychological & Philosophical issues – Should we really be targeting higher areas of Maslow’s Hierarchy of Needs
- Educational & governmental changes – Similar to above but more impactful, how will Educational systems need to change to prepare tomorrow’s students for a world changed by AI?
Whilst I still have very cautious optimism of the use of AI in the world and workplace I feel that no one is yet ready to fully embrace the change it will bring. More importantly I do not think the Australian government or educational system is ready for the economic changes that the rise of automation will bring and is already starting to bring. I say this not for impact or sensationalism but because it’s only a matter of time until the workplaces see the effects!
Further links for review about this topic:
- MCKINSEY GLOBAL INSTITUTE – JOBS LOST, JOBS GAINED: WORKFORCE TRANSITIONS IN A TIME OF AUTOMATION
- Yes, robots will steal our jobs, but don’t worry, we’ll get new ones
A slightly different blog post today, I hope you’ve enjoyed reading it as much as I have in attending and learning more about the advance of AI in the workplace and the world. If you’re interested in the Data Science Breakfast meetup Sydney, it can be found here: Data Science Breakfast Meetup