How AI and machine learning will shape the workplace
As a Sci-Fi fan, I watch many movies that showcase Artificial Intelligence (AI) in the future, and usually the narrative becomes one of humans battling machines in a race to survive. Granted this isn’t always the case, but it seems to happen more often than not. This causes many to question the ethics of AI and whether we should be pursuing our attempts to create something that has the potential to advance beyond what we are capable of. I think the point where AI will advance to that state is still some way off, but that is a topic I will cover in a later blog, especially around the ethics of AI.
We do however have interactions with AI and machine learning now that help to make our lives just a little bit easier. Let me give you an example; my wife turned to me after she’d finished her call somewhat puzzled, saying that the person that called her wasn’t a contact in her phone, but the phone suggested that the call might be from “John Appleseed”. She then asked how the phone could know who might be calling.
I explained to her that her phone will search through messages and emails and if that person‘s number and name appear together in any of these places a number of times, then through Machine Learning and AI, it can make reasonably accurate predictions.
My wife was quite taken about a back by this as she started talking about Big Brother, privacy and security but I do think that these capabilities and functions in our technology do help to make us more productive and improve our user experience. AI and machine learning also play an ever increasing role in the workplace.
The office I working in has multiple technologies that come together to form a modern workplace. As an example we have digital signage giving us messaging and updates on what’s going on in the business, we also have meeting rooms where we can either use monitors to project content from our devices or we can use video conferencing to enhance our remote meetings.
We have the ability to hot desk across multiple floors which can lead to the issue that if you don’t get into the office early enough, or if more people decide to work in the office than normal then it can be difficult to find a desk.
The biggest challenge these technologies and capabilities have is they are mostly disparate and disconnected thereby reducing the productivity and experience of users. One of the things I believe will happen in the medium to long-term is the consolidation of these technologies coupled with AI and Machine Learning will provide a more cohesive and coherent experience, let me give you an example.
If I get up at 6 o’clock in the morning my phone will tell me that the journey time to the office will take me an hour and 10 minutes. If I get up at 7 o’clock, the phone will tell me that the journey to the boys school will take 10 minutes, so clearly my patterns are being learnt and understood by my smart devices.
Now imagine this capability being connected to all of those ecosystems and technologies in the workplace. Imagine that when I get up at 6 o’clock in the morning and my phone tells me that the time to the office will take an hour and 10 minutes and I simply touch or confirm by voice that I am going into the office, it automatically books me a hot desk (or tells me there is no space to save a wasted journey) as well as booking a video capable meeting space as by looking at my calendar the AI determines that I have to do a video conference later on in the day.
Then as I walk into the office, either CCTV using facial recognition or proximity using the device I carry, the Digital Signage changes to tell me where my hot desk is and what meeting room has been booked for that day. As I approach my hot desk the chair automatically adjusts to my preferred settings along with that the monitors and keyboards altering height, brightness etc to my usual settings.
We can see how this kind of experience will change the way that we use our workspaces as AI, Machine Learning and connectivity between ecosystems adapt and evolve over time.
When we think about the technology and interconnections across systems that are required to realise this outcome, we see that architecting the systems or choosing the solutions that we deploy will become a much more holistic task, and require both our own organisations and those that we work with to have a broader skill set and capability than ever before.
AI = Smart?
I attended the ISE 2020 show last week in Amsterdam where we discussed topics such as 5G and Edge Computing, AI and Machine Learning, Smart Cities, Smart Buildings and the increasing role that human centric design will have in all of these solutions.
I’m planning to blog more about these topics over the coming weeks as they are each huge topics in their own right, but I think for the short term, we will see more and more capability being put into Buildings, Workplaces, Cities, Cars, etc. Machine Learning and AI will be integral to this. The danger sometimes is that we try to be too smart and over engineer or create solutions that are either too difficult to use, have no value to the people that use them most or are just not cost effective.
When designing solutions ask yourself what is the problem we are seeking to solve? Or What opportunities can we create? And think also about what behaviours will change or need to change. Using our intelligence coupled with Artificial Intelligence and Machine Learning will give us the best of both worlds and a future where we aren’t being hunted by robots.