TV and film are great indicators of what is grabbing the public’s attention. Recent box-sets have brought us Breaking Bad, Game of Thrones, Mad Men, House of Cards, Homeland and more. Within this plethora of screen time fodder, Artificial Intelligence (AI) has featured heavily; think of ‘Her’, ‘Humans’ in the UK, Sky Atlantic’s ‘West World’ as well as the older ‘Terminator’ movies, ‘Blade Runner’, ‘The Matrix’ and more. We’re very captivated by AI and the moral and human dilemmas that come with it.
For the sake of this discussion, I’ve grouped a number of fields such as advanced search, natural language understanding, machine learning, and deep learning under one heading of AI. Collectively they create a new breed of intelligence rooted in devices which will change our way of being. The cultural impact of the technology rather than the technology itself is the main focus of this piece.
The reality is that the majority of AI offerings will not be of the human form, and they won’t come as fast as much of the popular press will have us believe. We will, however, continue to see a steady automation of human tasks that require a certain amount of artificial intelligence to make decisions. Some examples of how machines are making our lives easier are:
Digital Assistants
- Siri, Alexa and Cortana all are intelligent digital personal assistants who help us answer our day-to-day questions, play music, switch on the heating, and add items to shopping lists. With 50% of searches expected to be via voice by 2020 (ComScore), that’s a significant amount of ‘machine’ help.
Discovery
- Apps like Spotify and Netflix are learning about consumer preferences and continually refining recommendations on what to watch or listen to next. Consumer behaviour trends are evolving from randomly ‘searching’ to ‘discovering’ things of interest through social media feeds. AI is all set to feed that trend adding more and more intelligence to what is recommended to us.
Face recognition
- Facebook and other photo apps now recognise your friends and the Microsoft Surface Pro 4 uses facial recognition instead of a password (love that). There are no humans involved in any pf those processes. Although the Facebook part is fun, the same artificial intelligence is being used to take this further by identifying tumours and cancers in MRI scans.
Large scale data analysis
- Businesses are collecting so much data these days that there is no way to process it without some help from machines. Think about the fraud alert calls you get from your bank when you visit unexpected places. That type of service, to decide when to call you and when not, is only possible because of AI.
Chat Bots
- This is also true for customer support, you know those chat bots at the bottom of the screen in a chat box? A lot of those are AI programmed to answer rudimentary customer queries.
So what’s next?
That intelligence will evolve and help us with more of the repetitive tasks happening in the workplace that can be turned in to algorithms and programmes. Insurance underwriting is one of the most talked about areas for future automation, taking over many of the repetitive process steps.
We’re also seeing the impact in supermarkets as tills become automated. Amazon’s Go store in the US is jaw-dropping in terms of a shopping experience as you don’t even go to a till and it will be interesting to see how consumers react to such changes.
The recent McKinsey study on the topic of automation and AI estimated that with the current technical offerings already in place, 49% of workplace tasks could be partially automated. However only 9% of work is a candidate for full automation and the rest would still require a combination of human / AI oversight.
Driverless cars are the most cited example of the social leap offered by AI. Google’s Waymo pages provide an argument for their use to remove the human errors such as speeding, drink driving, distraction and drowsiness. Human weaknesses, they say, contribute to 94% of crashes in the US.
Health is a further opportunity area with at some point machines presumably being able to perform minor operations. So it’s coming, but is it coming as fast as popular culture would have us think? I would argue there are a few non-technical challenges we’ll need to work through first.
What will we go for?
There are so many opportunities around AI, but we don’t know yet which ones will get the consumer buy-in. Remember when we were all going to drive around in Sinclair C5s or cruise the streets on Segways? And how Betamax was better than VHS but VHS won out? Well that’s where we are. We need to find out which of the many offerings are going to be useful to the already overwhelmed consumer. Currently, AI developments are both disruptive and explorative. What we as consumers will accept in a wider market place is yet to be seen.
Job shifts
When large organisations start to exploit the AI opportunities on a large scale, there is a big people change challenge to resolve. Automation will take jobs away. There will be resistance from employees and that Industrial Relations challenge will slow things down massively. We’ll also see that Legal & regulatory teams will need to include tech people as the challenges will be significant. Organisations need talent strategies that analyse where processes will change and what skills need to move or be developed.
Jobs won’t just disappear – they will move and decant into other areas. A great example of this is that visual effects professionals, who have been recreating our world on screen, are now being employed by the AI industries. Using their skills and data to help the machines learn from the images they built for the movies. In the field of medical surgery machines can learn about the human body from how it’s been modelled in special effects.
The better positioned businesses will be the ones that recognise opportunities to reconfigure its workforce earlier rather than later. Understanding the business implications of new technology and making the people plans to transition people (see my previous post on cultural architects).
Societal level challenges
How will society cope with the increasing automation is also a big challenge. Countries get richer, but these days that doesn’t necessarily create jobs. Even with movement, society is going to be faced with fewer manual jobs, so how are all these people going to earn a living? Lets take the impact of driverless cars as an example.
Although there are huge logistical and planning challenges to get in place before the technology of driverless cars can be integrated into our towns, it’s perhaps lorries (their routes are more standardised) rather than cars that will be the first areas to use of this technology.
A google search says there are 3.5 million truckers in the US. What if all of those were out of a job within 15 years?? How to handle this, and how to distribute money so that the wheels can keep turning is a question for governments and economists. Will governments tax AI and how will that tax get channelled back in to the society? All big policy questions that will vary in their complexity and considerations as you move from country to country.
The changing consumer relationship
The consumer relationship is going to change too with AI. Consumers will shift from dealing with traditional product and service providers to having new deeper relationships with the suppliers of the devices. Something that gets increasingly psychologically complex as these devices become more human.
Our relationship will more likely be with Apple, Amazon Alexa, Siri, FitBit or others like them. Our relationship will also be more personal and more localised. And will they be an relationship manager for other services? Probably. An interesting challenge for marketers.
Who owns your data?
Then you get in to data issues. Think about the amount of data those devices have on you?
- There is your phone, Facebook, and your photo store providers. All of these know who you are, where you are, who you are with, what you look at online and what you buy.
- Amazon Alexa is listening to you all the time waiting for your call, switching your devices on and answering your questions..
- Your Fitbit is on your body and knows your heart rate, sleep patterns, messages, and exercise regime.
- Uber knows where you have been, where you are going, and when you’ll pay more and when you won’t. (BTW interesting aside – did you know Uber drivers rate the customers too? It’s well hidden in the app but check out this link to find yours, mine is a smug 4.64.)
It’s fascinating and eye opening to think that google is a faster predictor of flus and viruses in the UK than the NHS. Data has huge opportunities to make the world a better place, but it’s also scary. Who owns our data, and all that intelligence on us, and what are the rules on combining it, sharing it or using it?
Do consumers want Facebook, Amazon, Apple to own all that? Consumers are now (possibly without noticing) using Facebook, eBay, and google to identify themselves across numerous sites using one federated login. Will there be a tipping point where consumers start to take a greater interest in their data? Something that may become more likely with the advent of GDPR in May 2018 (a new data protection framework for the digital age based on a consumer opt in model that all organisations will have to adhere to or risk huge fines).
Thinking about the people strategies and in-house skills around AI in order to have the workforce in place to deliver to consumers will be challenging. The people change around AI is definitely going to be harder than the technology change.
The Business Transformation Network has posted this article in partnership with Making Change Happen blog.
