Algorithms are not Artificial Intelligence

Last week, the TUC released a report calling for more worker protection from the use of Artificial Intelligence, the latest technology area to become part of the mainstream. They cited issues that are already causing problems in the workplace. But are they talking about the wrong thing?

In recent years, the use of technology has become more prevalent in the workplace. One area where this is particularly true is in the field of Human Resource Management (HRM). Specifically, the use of algorithms and Artificial Intelligence (AI) has become increasingly popular for making decisions about employees. However, there are important differences between “management by algorithm” and the use of AI in the workplace that employers need to understand.

Management by algorithm refers to the use of pre-programmed rules to make decisions about employees. For example, an algorithm may be used to determine which employees are eligible for a promotion or to decide which employees should be let go during a downsizing. In this approach, the algorithm is designed to apply a specific set of rules to data about employees, without any human intervention.

AI, on the other hand, involves the use of machine learning algorithms that can analyze large amounts of data and learn from it to make better decisions over time. For example, an AI system may be used to analyze employee performance data to identify patterns and make recommendations for how to improve performance.

One of the key differences between management by algorithm and the use of AI is the level of human intervention involved. In management by algorithm, there is little to no human input in the decision-making process. This means that decisions are made purely based on the rules that have been programmed into the algorithm. However, in the use of AI, human input is still required to train the AI system and ensure that it is making accurate decisions.

Another important difference is the level of transparency involved. With management by algorithm, the rules that the algorithm uses to make decisions are often not made public. This can make it difficult for employees to understand why certain decisions were made and can lead to a lack of trust in the system. In contrast, the use of AI is often more transparent, with the system providing insights into how decisions were made and allowing for feedback and adjustments.

Additionally, there is a difference in the potential for bias. Management by algorithm can be more prone to bias because the rules that are programmed into the algorithm can reflect biases that exist in the workplace or society as a whole. However, the use of AI can help to reduce bias by analyzing large amounts of data and identifying patterns that may not be immediately obvious to humans.

In summary, while both management by algorithm and the use of AI involve the use of technology to make decisions about employees, there are important differences between the two. Employers should be aware of these differences and carefully consider the potential benefits and drawbacks of each approach before implementing them in the workplace. By doing so, they can ensure that they are making informed decisions that support their employees and their organization as a whole.


Over the last few weeks, there seems to have been a welter of articles and events on the changing shape of work and –  as a consequence – how we need to throw our models of change and organisational design out of the window. Whether it’s the robots coming to take our jobs, the gig economy, globalisation or Brexit, everything’s changing and we’re living in scary new world where nothing is certain.

Except perhaps it’s not changing quite as much as we think. For example, recent data suggest that the rate of increase of the use of robots has actually slowed across Europe in the last five years and is at a lower rate in the US. That might speed up again but even now is only at a level of 2.5 robots per 1000 workers.

Similarly, the gig economy – as recognised by a recent CIPD report – still only forms a small percentage of the workforce, most of whom remain in traditional employment relationships. Even if we extend that to all self-employed workers, despite the growth in recent years they still only form around 15% of the working population.

I’ve been hearing about the impact of the VUCA world for at least 5 years now. Looking around, most of the organisations I work with are still structured in a very similar way to the way they were in 2012 – and I suspect they will not look that different in 2022.

The reason – humans adapt slowly to change. The technology to create driverless cars may exist, but until they are socially accepted they won’t take off. And that won’t be until numerous ethical and political issues are resolved. How many people talk to Siri/Cortana/Alexa currently? A growing number, but still only a tiny minority. Many humans find the idea of conversing with an inanimate machine a difficult concept. It will come no doubt, but over a longer timescale than the proponents suggest.

So while we should review our models and theories of change (particularly dumping the outdated Lewin model in the dustbin of history) we should remember that change will be controlled by the speed that humans want it to – not simply by the fact that we have the ability to do something.

The Emperor’s New Clothes?

Last week I needed a taxi to Lime Street station in Liverpool at 530am, so I tapped an app on my tablet and within 5 minutes a car was outside my front door. Chatting to the driver he told me that he chose the hours he worked and he tended to work 5 in the morning till around 230pm as it allowed him to pick up his children from school. As we pulled up at the station he pressed a smartphone screen on the dashboard to accept his next job from the taxi firm.

Was I using Uber, the “disruptive” firm that is now apparently the world’s largest taxi company? No, simply the same local firm I’ve used for the last 20 years. Their drivers are all self-employed, use their own cars and pay a weekly “settle” to the firm for the work that is pushed their way. Probably the only difference is that the company still operates a small office so that if you are not smartphone savvy you can ring for a taxi.

Which is why when I saw this graphic being tweeted it brought a wry smile to my face.


I think we’re meant to think “wow, aren’t these companies radical and different?” But in truth, they aren’t. What they have done is to use technology successfully to minimise costs and to trade more easily across international boundaries, but otherwise they are little different to traditional models.

Let’s look at some of the others. Facebook – “creates no content”. Neither do most cable/satellite TV channels – they are simply media platforms which generate income by selling advertising. Where does Facebook get most of its income? Advertising.

Alibaba – well here’s how it works: you pay them a fee to have a presence on their site and then sell your goods. Sound like a giant fleamarket or car-boot sale? That’s because that’s what it is. Markets don’t hold inventory either.

Airbnb – back in the 90s I used to get a brochure for “Rural Holiday Cottages”. Some were people’s homes they’d let out for a couple of weeks, some were renovated farm buildings, but they were all available to rent for a week or fortnight. Rural Holiday Cottages charged a fee to advertise them but didn’t own a single one. Again, the Airbnb model – they just operate on a global scale

And what’s this to do with HR? Well, if business isn’t really changing – merely incorporating new technology – then the skills, knowledge and practices that HR people should use probably haven’t really changed either. We may need to react faster and jettison some cumbersome procedures (and perhaps even use new technology) but the fundamentals of good people management remain the same.