What I learned at the inaugural #WomenInLearning conference

I was highly appreciative and privileged to get a late ticket to the first #WomenInLearning conference last week.

When I’m at events like this, my bias is to share the insights as best I can. I try to honour the speakers for their content as much as I can and offer my stuff in addition to what I hear. So I live tweeted the event. You can catch the complete thread here. Better than that thread, though, is the actual #WomenInLearning hashtag which has everyone’s contributions at the event.

We live in an age where it’s becoming easier to identify where there is unfairness against women, what kind of societal norms prohibit and reduce the progression of women in the workplace, how discrimination both knowingly and unknowingly takes place, and just how much privilege there is to just being a man. This doesn’t mean that men have it easier than women, it means that the barriers to ease are less than they are for women.

And for the sake of completeness, I think it’s fair to say this event was addressing exclusively bias against women. It did not look at bias against any other group. There’s a good reason for that, too. The event came about as the result of a survey carried out by Donald Taylor a few years back where he sought to understand the gender difference at senior levels in L&D. The results showed that only 31% of senior roles are occupied by women. From a sample of 2635 respondents, that’s fairly representative.

From those results, several conversations carried forward to a group of women – Kate Graham and Ashley Sinclair, deciding further positive action needed to be taken. (I’m sure others helped to make things happen, I just know these two did a good amount of PR and marketing.) How do you have a positive and progressive conversation about why there aren’t enough women in senior roles in L&D without it becoming a man bashing or destroy the patriarchy event?

You hold an open conference where men and women are invited to attend. I think in the room there were probably about 15-20% men in attendance. It might have been lower than that.

The speakers were chosen really well.

It was fascinating listening to Nicole Kilner, the CEO of beauty company Deciem – a $300 million global business with 800 staff. Oh and by the way she’s only 30. She shared some fascinating insights into how she leads and how she shows leadership to her whole team. In her company, they’ve chosen to use a combination of Thrive Learning and GetAbstract to provide learning solutions to Deciem staff. Instead of off the shelf content on leadership insights, Nicola and her team have recorded videos to be shared with their company. In her opinion, if you’re going to hear about leadership why hear it from people that have nothing to do with your company?

I loved hearing from Julie Brayson, Head of OD at Card Factory. When I think of how to use my platform when I’m speaking st conferences, its Julie’s example I recognise as being necessary and highly effective. Julie left school with no formal qualifications. She went on to work at a retailer who sent her ok workplace training to improve her skills. She learned that she wanted to be a trainer and thus began her career in L&D. Several roles and years later she’s now heading up OD for a national card retailer and later this year will take up her first Exec Director role. A far cry from being told that because she didn’t take typing at school she wouldn’t get a job as a secretary.

Catherine Cape shared her story of how she left school to join en estate agents where she first went on workplace training. And she, too, was inspired by the trainer. She shared that when as a woman you ask for what you need – a promotion / a raise / more experience, it’s not being pushy or demanding. It’s recognising your needs and honouring that. She told us that she’s fortunate to have a husband who supports her being the main breadwinner. Pretty fantastic.

The event finished with a panel of Jane Daly, Chief Insight Officer at Towards Maturity, Kristina Tsiriotakis, Global Director L&D at Deciem, and Catherine Cape. This was nicely done with the audience rating the questions they wanted the panel to answer. I do love good use of tech at a conference. And on that point, the use of menti.com is well worth checking out for your interactive audience needs at a conference.

Also, we found out Don doesn’t know what Percy Pigs are (they’re soft sweets from Marks and Spencers).

The conference was really helpful for my own learning in this space. As a man, I’m going to be mostly unaware of the day to day barriers and everyday sexism that women have to put up with. I try to do what I can in this space and a very recent experience tells me I have a fair amount to yet understand and be better.

What stood out for me from the women speaking on the day was their personal experience they shared with us all and what they’ve learned about themselves along the way. We all of us battle with narratives given to us from our younger years and have to find our way forward. For women, these narratives are often reinforced in many direct and indirect ways. As men, we can do a lot to just listen to the experience of women and understand it better. That’s why I went to the conference – to just listen. It can be really easy for men to feel they need to have to interject and comment on everything they hear. I’ve learned my voice is not needed in many situations – even those where I’m leading or facilitating a session.

There’s more to be done in this space. More for men to understand the experience of women in the Learning profession. More to do to actively seek to develop the progression of women into senior roles. More to be done to reduce gender bias in the profession. More to be done to raise empathy. More to be done where we have strong representation of women in decision making roles.

What happens when tech helps imitate human movement?

At the CogX event I attended a few weeks back, I went to a session from the CEO of CTRL-labs, Thomas Reardon. He was talking about Neural Interface and The Future of Control

This was a fascinating talk, absolutely cutting edge stuff. When I think about the potential of tech and how it can enable or progress human development, this is the stuff which is gonna make that happen.

Thomas gave some really great context about his talk. He said that the research they were looking into was not focused on the brain. They found that when you try and determine which part of the brain is responsible for moving different muscles and body parts, it’s not as clear cut as it may seem. Different parts of the brain activate and you can’t localise enough.

So when it comes to creating an ‘interface’ for the brain, they chose not to go near the brain at all. They didn’t want to plug an electrode or connection into a brain and hope it achieves what they want.

Instead they found that the electrical impulse sent to a muscle can be measured. You can wear a wristband or other attachment to measure electrical activity, and determine exactly when the brain is sending a signal to the muscle for it to be moved. Effectively that signal is a kind of binary – muscle activated / muscle not activated.

What they’ve done with that knowledge is create a VR simulation of your hand as an example. By wearing this wristband on the arm, you can control what the hand is doing in the VR simulation by ‘willing’ it. The brain sends a signal to the arm to move muscles in your hand, and the exact same movement is replicated in the VR simulation.

They took this further and asked someone with no fingers / limbless arms to wear the band and see what they could do in the environment. Those people could still control the VR hand as if it were their own. Imagine that. Imagine not having a hand, but by wearing a device you can mimic in a virtual environment the exact movements you want your hand to make.

Thomas highlighted this further by asking someone in the audience to drink from a glass of water. He described that that ‘simple’ act is actually incredibly complicated. You are automatically adjusting for multiple factors. Lifting of the glass. Moving the glass to you mouth. Drinking from it. Readjusting your grip based on loss of water in the glass. Placing it back down so it doesn’t smash. And it’s all done with very little active cognition. Meaning, I’m not actually thinking about the act of drinking water, I’m just doing it.

What this highlighted was that the complexity of human movement isn’t something that can be easily achieved with robots. Through a VR simulation, though, you can manipulate in such ways.

Additionally in the VR environment you can mimic the force of the virtual grip i.e. if you wanted to create a tight fist and create a lot of force, that would be replicated.

An unexpected result, was that the programme could identify the user based on them wearing the wristband. It recognised the electrical impulses as unique to that individual. I think that’s pretty fascinating. It essentially means we have another kind of unique identifier in our electrical impulses.

The application for this kind of tech is more readily understood for people who suffer motor diseases / conditions e.g. ALS or cerebral palsy, or those who are limbless. Imagine having a condition like muscle tremors and not being able to voluntarily stop, but in a virtual environment you experience none of those kinds of involuntary movements.

Thomas was also a very good speaker. He clearly knew his subject well, and was well studied in the area of neuroscience and gave a lot of clarity about what he was and was not seeking to research and therefore manipulate.

AI, financial crime, and learning

Be warned. This is a long blog post.

The question of learning is a deeply fascinating one.

What does it mean to learn? What are the processes for learning? When we are learning, what is happening to us and for us? What can we learn? What can’t we? Can some people learn more than others? What does it mean to have learning difficulties? How do we enhance learning? Is there a limit to how much we can learn?

It’s these kinds of questions that many people are trying to replicate in discreet form with artificial intelligence. AI being that which doesn’t happen naturally. A system can be created and programming written that allows for elements of learning to take place.

Probably the best known example of this currently is in chess. When a machine defeated a grand master of the game. Someone deeply skilled and knowledgeable about the game. Arguably, though, this wasn’t genuine AI. This was machine learning at scale. The coders at IBM of Deep Blue simply fed the machine 1000s of iterations of movements and let it play continuously until the machine learned which moves would be calculated and create a winning outcome.

Whether we’re talking AI or machine learning, what we’re discussing here is the handling of data at massive scale, optimising an outcome, and having the capability to share that with other connected networks so you have a vastly improved and efficient system. This is one of the ways Tesla is able to be so successful. Their self-driving cars take the hive mind approach. If one car is involved in an accident, the engineers will interrogate the evidence, re-write that part of the coding and deploy to the whole fleet.

Ok. With me so far?

$2 trillion. That’s how extensive financial crime is globally. It is a staggering number. Just immense.

1%. That’s how much is stopped/caught. Just 1%.* It feels like nothing. Not even a dent.

One of the problems is that criminals carrying out financial crime in the digital age are using processes like AI and big systems to create coordinated efforts of crime. Not just hacking banks, but creating fake bank accounts, funneling money, identity fraud. It’s proper scary stuff.

Banks and financial institutions and credit agencies are trying to make things secure. And they have good processes in place. But what they can’t cope with is the scale and multi-coordinated attack.

If Criminal 1 decides to create a fake account at Bank A, there’s a chance they’ll get caught out. But if Criminal 1 uses Fake ID 1-2000 and submits all that to Banks A-H, you’ve got numerous permutations of the ways that data can be submitted and checked. There’s a high likelihood most of those applications will just be accepted.

The human processes we have in place can’t operate at that scale. We are restricted by our individual capacity. Even with a group of people, you’re still limited in what you can achieve.

There are also limits on how the data being received by these companies can be shared amongst one another – simple answer it really can’t be shared easily due to GDPR. These institutions have to find other ways to collaborate to reduce the scale of the attacks they face.

This is one of those examples where AI can be used most effectively – but we’re at proper early doors with much of the collaboration happening in this space. We know the kinds of markers to look for: account activity which looks normal but isn’t, fake ID, abnormal transactions. What we also have is plenty of people data: why do people open bank accounts, how do they use their accounts, what kind of activity do they carry out, demographic data, personal data. You can quite accurately predict the lifestyle and demographics of an individual from their online activity.

Now take that individual data and put it at scale. Hundreds of thousands of people’s data available to be monitored. You can identify so much around normal behaviours that identifying outliers becomes more sophisticated. Banks et al are then better able to work with law enforcement to provide them insight into what problematic behaviour looks like and how they can detect it.

It’s all very impressive stuff, and worryingly we’re a long way off reducing the level of financial crime we’re already facing. The scale of financial crime is only set to increase over the coming years. If we can’t counter $2 trillion worth of financial crime today, how will we detect and stop bigger activity in the future?

So, being the L&D minded guy I am, I started thinking about the application of AI / machine learning to our common learning problems we face.

If AI can spot patterns of behaviour and create models of behaviour for discreet instances, how could we use that for learning scenarios?

One way I think is by identifying learning behaviour at work. At what point does a worker need to know something? What kind of behaviour do they engage in which prompts them to search for a solution? If they go online, what are they searching for? If they get answers, where are those answers coming from? If they’re getting answers which are immediately helpful, what’s the impact on their productivity?

I don’t think we genuinely understand what learning behaviour at work looks like. We know from surveys and interviews what people do, but we’ve not really got a way to focus on actual learning behaviour. If someone reads something, how long are they reading for? If they’re watching a video, how long do they watch for? If they’re doing multiple searches for a problem, when do they give up and try alternative options like talking to someone?

There’s a level of understanding patterns of workplace learning which we make a lot of assumptions about and have our own conclusions. What we lack in nearly every instance is the actual data led behaviour.

Once you understand the patterns of behaviour, we can start to use the same techniques to provide solutions at the point of need.

Now let me be clear, I believe we’re a long way from being anywhere close to this kind of intervention. L&D aren’t ready for it. We just about accept virtual training as a credible method of learning solution delivery and there are 1000s of L&D/trainer types who are very invested in their own models and interventions. Most couldn’t work with actual business data, let alone patterns of behaviour and deriving computational models of improving performance.

Also, I’m not talking about our companies using AI. I remember being at a conference 2 years ago with heads of L&D claiming they were using AI. They weren’t. Their companies had started introducing AI engineering into their processes, but the L&D teams themselves weren’t even close to it.

And I’m also not talking about smart algorithms via machine learning about “suggested content”. Yes, it’s very clever to detect patterns of content consumption in a particular system, but that’s a discreet use case.

What I’d love to see happening is understanding workplace learning behaviour at scale. Not just what does it look like for tens of thousands in a workforce, but for hundreds of thousands across sectors and industries. That would be genuinely fascinating data to be able to work with and create targeted learning solutions for each pattern and identifiable need.

The clever thing about the crossover of data science, AI and machine learning is that we have a lot of good understanding of these things in many companies. That learning, can be taken and applied to many more situations and enable some really impressive learning solution design.

*This was quoted at a CogX panel I attended last week. I didn’t catch the reference point for it.

I could be very wrong about the examples and terminology I have used above. I am not studied in AI at all, and this piece was written as my reflection from attending CogX 2019 as a way to increase and improve my own learning. I am very happy to be corrected on anything I have stated incorrectly.

The day I didn’t go to a learning conference

Last week I decided to go to a very different kind of event. I registered to head over to CogX in London. CogX is an expo event where they talk about AI and the future of tech. It was seriously impressive stuff.

First of all, the event was held at Kings Cross. Not a conferencing venue in Kings Cross, but the whole site. I loved that. It was a proper Expo. Different zones, marquees all over the place, volunteers everywhere, and very well thought through user / delegate experience.

As with most big events like this there was a mix of free sessions and conference paid for sessions. I only signed up for the free sessions, and I’ll write about those separately.

What I enjoyed the most, was the genuine exploration and explanation of certain use cases of AI and of Tech.

In the case of AI the speakers were discussing financial crime. I didn’t realise the scale of financial crime globally (estimated at $2 trillion). How does AI fit into this world? By helping banking and financial institutions handle data at scale. If you have 1 evil person wanting to create a false account in a bank, there are checks and balances to highlight if that person is evil or not. If you have a coordinated group doing this at 2000 different banks, the vast majority of those false applications will get through the system without problem. An AI system can strengthen the checks and balances across multiple banks to identify if there’s a coordinated effort taking place which through human efforts may go completely unrecognised.

Interestingly, AI can also more acutely help with personal identity and verifying if the proof of ID you’re submitting is genuine or not.

In a very different space, I attended a session where the speaker was describing how tech can enable people who are limbless, or have physical conditions which dramatically complicate their muscle movement – ALS / cerebral palsy as examples, and use a VR environment to facilitate an actual limb being moved. This was genuinely fascinating.

The speaker was careful to make the distinction he wasn’t talking about brain science but of motor neuron signals. And he made this distinction because when studying signals to muscles it is possible to detect when that happens at the point of the muscle. What’s incredibly difficult is to know which part of the brain is sending the signal. So his company is not interested in localising the part of the brain controlling muscle movement, but the point at which a muscle receives the signal to move.

Based on that signal, they can create a 3D image on a screen of a limb and imitate the movement you want to make just by sending signals to the muscles of the arm. A transmitter on the arm reads the signal and interprets it accordingly.

It was genuinely fascinating from a tech and human development perspective where the tech is being used to enable people who do not have limbs / cannot control their limbs to potentially experience those things in a virtual environment.

The nature of CogX is for it to be an Expo. That is fundamentally different to a conference and exhibition event. What I was left with was that the exhibition format is seriously tired. The Expo had proper prototypes for people to try stuff. Not hear a case study about how the vendor’s approach to a business problem achieved success. That’s just not interesting. A live simulation of what can be experienced? That’s powerful stuff. In a traditional exhibition event, you’re being sold to. The human connection, the balance of big banners and posters and smart screen stuff is difficult to weigh against just not doing it and opting for something radically different.

I’m glad I purposefully stepped out from the normal L&D/OD big event stuff and experienced something fundamentally different.

Why L&D need to be at more HR meetings

I hear it regularly enough. I’ve written about it previously. And yet it’s still a topic which gets refreshed. HR bashing is a thing. Oddly, many in L&D seem to want to do it just as much with no irony that the business views the two as the same and so you’re bashing yourselves?

And I’ll hear it regularly still.

I’m not HR. Never have been. Never will be.

HR don’t know what they’re doing, I’m glad I’m not part of then.

We could get so much more done if it wasn’t for HR.

It’s almost like there’s a parallel here for tribes, or nations, or pretty much any grouping in human history.

And here’s what I’ve learned from being in organisations where there’s a whole mix of ways that L&D and HR are either part of the same teams or not.

1. If you’re not in the same team, find a way to have regular conversations with your HRBPs. They have a whole fountain of insight and knowledge about their part of the world which is invaluable. They’re having conversations with business leaders you’re not having. By having regular conversations with your HRBP you learn what’s important to them, understand what they’re working on, and can offer solutions and L&D support. In all likelihood you’ll get invited to do stuff with that part of the business and the business leaders.

2. The broader HR process stuff is important for organisational effectiveness. The annual performance review process, the employee engagement activities, performance management and ER, recruitment – and in many cases L&D is owning the responsibility for many of these things. If you want those things to be better, get involved in them. Lead on them. Provide leadership and your thinking. That’s how change happens, not by sitting on the outskirts and bitching.

3. Influence can only be a thing if you’re present and taking ownership of what’s happening when you’re talking to business leaders. If business leaders are bitching about HR, don’t join in the bitch fest with them. Instead listen. Just listen and let the business leader know you understand what they’re saying and you’ll talk to the HRBP about your conversation. You’re there having a conversation about appraisals and they’re moaning about the system they have to use. You own that just as much as HR do.

4. If the system is crap and you can’t escape using it, then for now make it the best damned system for you to work with. And help HR find a better system. Do your research, talk to the vendors, get demos arranged. Influence, influence, influence. And until then, work out what the system does well. Focus on that and make it do that and that only. All the other things you need it to do but it can’t? Just find a different solution.

5. In most cases, L&D reports into HR. The business doesn’t care if you have different roles. Business leaders see you as one and the same function. So if you’re out there bad mouthing the function, be aware it says just as much about your character as the truth bombs you might be laying out.

6. In the world of social media, it’s easy to get people riled up by bashing someone else or bashing a function. People like Katie Hopkins make a living out of it. Many people agree with what she says. But she’s not the moral stalwart she portrays. I wouldn’t trust her word on many things. And it’s not because she doesn’t say true things. It’s because her truths are about the defamation and demonisation of others. I don’t want to be associated with someone like that in any aspect of my life.


Learning and training are entirely different things

I’ve been thinking lately about the methods of L&D that have been written and spoken about in the last 20/30 years. I’ve been writing this blog now for about 10 years. You can see the many topics I’ve written about in that time and they vary a lot. One of the consistent areas I’ve written about is the progression of learning theory and what we understand about learning. What regularly gets reinforced to me is that the design and delivery of training is normally what L&D is charged with and delivers. It seems to be more rare that anything close to a focus on learning is happening.

I get involved in the design of training solutions, and I don’t kid myself into thinking I’m providing a learning solution. What’s the difference, I hear many of you ask?

Quite simply this. Providing a training course is an information dump. It is made interesting and engaging and interactive through some quite helpful methodology, but there is little in the way of learning which takes place. This is mostly because learning doesn’t happen just because they’ve been on a training course. Indeed, many trainers will caveat their training with a variation of the following…

“This course will only serve to raise your awareness of this topic. You will have to practise in order to improve your capability in the topic.”

And if it’s e-learning…

“If you complete this e-learning you are helping the organisation remain compliant.”

A learning solution implies that the solution enables learning to take place. That solution could be any number of possibilities. It could be a coaching conversation. It could be reading a book. It could be listening to a podcast. It could be watching a YouTube video. It could be sharing your thoughts with someone else. It could be being incentivised to do the right thing. It could be positive reinforcement of good behaviour. It could be training to improve knowledge or a skill.

The move from a training course/e-learning to a learning solution is that you’re fundamentally asking different questions. Not just asking different questions, but also expecting different things from your suppliers/vendors.

Some of the vendors I work with and talk to are helping to advance a learning solution as much as they may want to sell me a training course/e-learning. They’re helping me to challenge what I’m doing and to provide more of a developed solution which isn’t just focused on the product.

And there are some vendors whose work I see and I understand that they are not interested in selling anything other than their methodology / product / ‘solution’. They say the right words when they’re ‘consulting’:

  • What’s your problem you’re trying to solve? What is it really? Is that the the right thing?
  • I understand your problem and can ensure the learning transfer will happen
  • In the training we can accelerate the learning so they improve their performance
  • We’ll design the e-learning so it has great UX and modern graphics
  • The e-learning will be bite size so it can be done quickly

Except these statements are examples of just being good at selling with the right words to sound like they’re offering something different.

And when I hear stuff around learning solutions? The language itself fundamentally changes.

  • What’s your problem you’re trying to solve? What have you tried already? What hasn’t worked before? What’s the right outcome? How will you get there as a leader?
  • Tell me about the way your team is currently working? When you’re done with the solution, how will you reinforce it as a leader? What processes will you need to have in place that you don’t now? How will the team reinforce their newly learned behaviour with each other?
  • How will this solution enable better business/organisational performance? What will other teams/leaders observe your team do differently they’re not doing now? What organisational outcome will improve because of this solution?
  • From this conversation, what do you want to happen next? What further thinking do you need to do? Who do you need to talk to in your team/amongst your peers/with your leader?
  • From all these conversations, is training still part of the solution?

This is a set of conversations which won’t stop in L&D. It’s a regular piece and is written about in many ways. Some advocate for training courses and e-learning like they’re being written off. Some advocate for resources and curated content as unheard of answers to problems we didn’t know we had. And in and amongst it all, many consultants are creating their own models, advancing their own theories and proposing new ideas.


What I’ve learned about getting buy-in

Relationships matter.

Over the years I get reminded of this at work in many different ways.

The way we talk to our work friends matters.

People get upset at work because relationships aren’t as they expected.

Our leaders provide leadership through the quality of the relationships they have with others.

Teams collaborate better because they have stronger relationships with some teams than others.

High performing individuals tend to be those who have strength of relationships to enable success to take place.

So I often have to remind myself that spending time to build relationships is a key way to get buy-in for my ideas and my things I want to get done.

And here’s some foul ups I’ve made along the way which taught me valuable lessons.

That time I was new to the organisation, sat through the induction, and immediately made judgements on what needed to change. I then proceeded to send out an email to all presenters from the organisation and let them know about the changes I wanted to make as the owner of the induction. I got an immediate backlash. I clean didn’t pay attention to the fact I spent no time before getting to know the presenters and their context and what they want new starters to know and understand. I just decided I knew best. Of course I knew little and had to spend time sitting with people and talking with people to understand their needs. From there we could move forward.

That time I decided the executives didn’t need that much of a briefing before an important programme launch. I was ready to just plough on ahead with my plan to roll out the programme and have the Chief Executice do the kick off presentation. I thought as an experienced business leader this would be a walk in the park for him. What I didn’t pay attention to was the importance of the briefing wasn’t to prep him for the kick off but to help provide assurance and context for what I wanted to achieve from the programme.

That time I needed everyone to complete CPD logs in a system. It was one of my first projects to get completed for the business as their new L&D Business Partner. I wasnt confident about what needed to be done in the system and had to try and corral very different teams to complete their entries. They didn’t know me and here I was sending emails asking for completion to be achieved or we risked losing our membership to this body. They did it and we got there but only because I realised I needed to spend time with the business leaders and get their commitment to helping me achieve this piece of compliance.

That time I didn’t openly share what I was working on and created distrust with my manager. I was going through some personal stuff and it was affecting the quality of my work. I knew it was happening and I couldn’t shake the guilt of not being productive and in delaying important deadlines and meetings. I eventually had a frank conversation with my manager about what I was experiencing and we could then have a conversation about improving my performance. That was hard and I realised I perform better when I let people know there’s stuff going on for me.

Relationships matter. They’re the bedrock of performance achievement in so many ways. I also know it’s a lesson I have to regularly re-learn.