In Part 1 we discussed how parallel memes, that technology is developing at a phenomenal pace and will enable widespread automation, and that humans need to become skilled at augmenting themselves with complimentary technical skills, are the key to answering the question of whether AI will eliminate CRE jobs. Now we will look at how to make sure it is not your job that AI eliminates.
There are four steps.
First, DO NOT stay in a job that involves tasks that are largely ‘structured, repeatable or predictable’. This extends beyond whether they are simply ‘1+1 = 2’ but includes anything where the inputs are the same each time, in general terms even if the specifics vary, and the outputs are also the same. If the task does not follow a pattern and/or requires judgement during the processing then you are probably ok, but if not…… watch out.
Over time AI will move ever higher up the ‘cognitive stack’. Machine Learning means just that; the machine learns through experience, so whilst a decade ago AI largely involved tasks that needed to be explicitly programmed, going forward this is becoming less and less true. Just think of a self driving car. There is no way every possible eventuality could be encoded into a system, so the AI must try and intuit ‘what would a human do’ in any circumstance. They are learning that by analysing millions of hours of driving by real people.
Secondly you need to learn how to think about AI. In 6 steps.
- Understand what AI is good for, and what it is not.
Knowledge, reasoning, planning, perception and communication are the five key areas that AI researchers have been working on since 1956. Reduced down to an essence you could say AI is about reducing the cost of prediction. What is the probability of X happening?
- Look for use cases’: 88% of the core tasks are ripe for automation’ said the AI report from the RICS last year. Over a ten year period admittedly but in some form or other those will be ‘structured, repeatable or predictable’ tasks. Look for the ones with the highest value first, or where your competitors are automating but you are not.
- Are these commonplace and repeatable within your own business and/or applicable to many of your customers? This is a numbers game to an extent. Find the tasks you can automate that are most common, or take up the most time. Not automating tasks that can be automated is just a waste of time.
- Do you have or can you obtain large quantities of data? AI does require data. Systems need to be trained and then tested, and that requires data to train on and data to test against. Humans learn by experience, so do machines. Data is what enables this.
- Are there clear metrics by which you could judge success? Working with data often throws up correlations that are not causations. You need to be able to assign metrics to outputs. You cannot learn if you cannot measure.
- If you have all of the above, is that something that will create significant value? Just because you can do something does not mean you should. Does the effort involved in creating this AI have significant value? If not, probably best to think of an easier solution. AI is not a trivial pursuit, so make sure it is worthwhile.
Thirdly in a world of exponential technology you need to become exponentially human. You need to develop all your human skills - of imagination, empathy, design, social intelligence, problem solving, judgement etc - because that is your value.
Do not try and beat the machines at what they are good at - don’t bring a knife to a gunfight. Instead work on how, with your understanding of AI, you can use it to augment your own human skills.
As prediction becomes cheaper, the value of judgment will increase. All this technology is an input: we are responsible for deciding the output we desire. Those with great judgment, who can weigh up upsides and downsides of predictions will see their value rise.
AI will give us more options: how we exploit them will be down to human judgement.
And think ‘education, education, education’ - in a fast changing world education is a marathon, an ongoing process. You will never run out of new skills to learn.
And then finally you need to deeply consider how AI/Data and all technological change is going to change the world.
There will be winners and there will be losers. Oftentimes each of us will be both. We will lose some things but gain others.
Mostly it is tasks that will be lost rather than entire jobs but there certainly will be many jobs that do become redundant.
There will also be a lot of real estate that becomes redundant: as the work we do changes the nature of the office is going to change fundamentally. Where and how we live as well. And as for retail, well there is much change coming there.
Pay attention to those four rules and your job will not be overtaken by an AI. In fact you will most likely thrive in an AI world. Either way though it is always wise to remember that it is not perfection you are seeking to attain: what you need to ensure is simply that you are better than your peers.
The AI juggernaut is coming, just make sure it is not you it flattens.