The deep bias facing L&D

As we continue our understanding of bias, prejudice and privilege in society, we also start to develop the capability of interrogating our own spheres. I have written before many times how there is a problem of diversity of people of colour in L&D. The most obvious place we can observe this is on the conference circuit. In the main, speakers will be white. It is incredibly rare to see Black people, Chinese people, Indian people, taking the stage. I’m not saying it doesn’t happen, I’m saying it’s rare. In the L&D space, it’s hard to find leaders who fit those demographics, and who are willing to speak on the conference circuit.

But that’s just one place where we can readily observe the lack of diversity.

If we think about things from a systems perspective, we start to see just how the L&D ecosystem is perpetuating completely and thoroughly white perspectives on the world, and it’s in every aspect of everything we experience. I’m specifically talking about L&D here – not the wider societal impacts of white thinking.

And I want to be very clear here – I am being critical of the complete lack of diversity in the system. I am not being critical of any individuals nor their thinking nor their contributions to L&D. In a lot of cases, we have very strong L&D thinkers, leaders, practitioners, consultants who design and deliver fantastic solutions and products. I applaud of all that, thoroughly.

What I am seeking to highlight here is that at the vast majority of our events that we hold, from the books that are written, from the speakers we hear, from the consultants who design, we are getting – in the majority – white perspectives. Yes, there are those who are of colour doing good work in our space, and they are in the minority.

What I see and experience is that we perpetuate and roll along very willingly with all this, and it seems like there is little effort to positively make a difference. White voices are heard, white voices make decisions in our profession, white voices determine the models and theories we follow, white people lead the vendors – do you see?

And let me be clear – I am not saying this makes any of us racist. It is just how it is. If we look at this more critically, it means we’re all complicit in the perpetuation of the same.

This isn’t about people of colour not taking the opportunities to present themselves, or put themselves forward – some already do that. It’s that through the systemic ways in which we operate, so much is done with a white person lens, that we willfully neglect and do not consider that there is a lack of any other voice other than the white ones.

What do I mean? When a call is made to the vendor and an account manager takes the call and puts forward the brief to their team. When a project needs to be managed and the project manager decides on the actions that need to be taken and who’s accountable for what. When a conference organising team is a handful of people. When the academics we laud and talk about and listen to and whose models and theories we want to learn more about. When the books we read are given accolades. When the awards are judged and the decisions are made about the winners. When a new product is launched and there’s a big marketing campaign.

In nearly every one of those scenarios, I’m willing to bet that there are more white voices involved in all of those scenarios than there are active voices from people of colour. I am not suggesting we stop working as we do. I am highlighting that the system enforces the voice of the white person.

This is the deep bias.

Our problem in L&D is that we think we’re above prejudice, above bias, above discrimination. We think we are more inclusive than most, more accommodating of needs than most, more aware of bias and prejudice than most. And yet, it would be tangibly very difficult for most of us to genuinely put forward multiple examples of where diversity bias isn’t so clearly lacking. I’m saying multiple examples because one or two examples from your own experience isn’t enough. I’m talking everyday actions, not specific moments in time.

Our problem in L&D is the same problem in society at large. We believe that our everyday interactions and actions are as genuine as they can be and that we’re treating people well. This isn’t about how well you personally treat others, or what you personally do to make a difference. This is about how the system at large is designed so heavily in favour of white voices that we don’t even recognise the lack of non-white voices.

And for completeness, we are woefully biased against so many other demographics, which I’ve not even tried to address here – disability, social class, sexual orientation, gender orientation, formal education or not, and so many more.

This is the deep bias.

There are no easy solutions here. I’m not asking for solutions. I’m also purposefully not proposing solutions. This blog post isn’t about that. It’s to cause debate. It’s to state observations which I believe to be blatant and very present. This blog post is to bring this discussion to the fore.

Discussing this topic won’t get you in trouble for being racist – unless you use racist language, or say things in racist and discriminatory ways. In the main, most of us will understand how to not do these things, so your contributions and thoughts will be welcome. If you’re not comfortable commenting in the open space, then DM me on Twitter or send me a private LinkedIn message. It is from discussion that we can keep things moving forward. When we don’t discuss things like this openly, we remain complicit in perpetuating the strength of white voices and do not do enough to include voices from people of colour.

Final Point – I hope in this writing you will have seen that I haven’t accused anyone of anything. I’m not singling out any one individual. I’m being quite measured in my language and the points I’m making. I am talking about the L&D ecosystem which is all of us.


The fine line of not being a psychologist

In L&D we have a long list of trainers and consultants helping to deliver services and solutions to clients in many ways. That can range anything from MBTI to leadership development to coaching to unconscious bias training to NLP.

Some of these have a sound basis in psychology. Others just don’t. There is a difference in understanding a topic so well that you can design and deliver training on it, and having read The Chimp Paradox and think you have a superior grasp on emotional intelligence, leadership or high performance.

There is a line we as trainers cross quite regularly where we start talking about psychology and how people learn or what makes people tick or how to be a better salesperson. And that line needs to be traversed everso carefully.

That ethical line is important and I fear too many just don’t think about the implications of the stuff they may think they’re sharing. What I mean to say is that too often trainers overestimate their insight into the human condition and believe they can support clients beyond just delivering training and crossing into being life coaches.

Trained psychologists spend years of their time learning their subject. And even then, they’re really only learning about one area of psychology. No one person can be well studied across all of psychology. And there are many areas – cognitive psychology, educational psychology, occupational psychology, counselling and psychotherapy, evolutionary psychology and much much more.

We can fool ourselves very easily into believing that because we’ve read books or watched a TED video or heard a speaker at a conference that we’ve got the same level of insight into the human condition – and sometimes even thinking we are better informed because we’ve read a range of things!

The challenge is to not get so confident about this understanding that you think you are a psychologist by default. Faux thinking around things like:

  • I understand how the brain works even though most neuroscientists can only give you specific information about specific aspects of the brain and I’ve never done any research into how the brain works myself
  • I understand how people learn because I can design and deliver training – they are not the same things
  • I understand how to enable high performance because I deliver training on coaching
  • I understand how people think even though there are many many theories about how people think
  • I understand how to influence people because I’ve read a book on how to influence people

I could easily go on.

And I’m cautious. There are those we work with who are genuinely well personally studied in the area of psychology. They have taken the time to really go deep with their thinking and their practice. They have valuable insight because of their deep study and thinking. I’m not talking about those people. They aren’t pretending to be something they’re not.

This fine line I’m talking about is when you have someone have so much self-belief that they just spout stuff which has little basis in actual psychological insight and is nothing more than their opinion.

There is a level of humility I think is missing from many who deliver training and try to delve into psychological topics of which they have a superficial understanding. To be able to understand when you as a trainer are entering into a conversation which you are clearly untrained for. That you don’t need to fake it to make it. That you don’t have to meet the need of the client in that moment because their need is for better support and intervention than what you can offer.

Professionalism vs Personal touch on social media?

A couple of weeks back, I posted this statement on Twitter >

It’s always hard to know what kind of response a tweet will garner. This attracted a fair amount of comment, from a lot of people in the L&D space. I’d recommend reading the many responses to the tweet.

What was I basing this statement on? The open nature of social media. What does this mean? I mean the way that social media means you are more than your brand, and we can understand so much more about each other based on what is available in the social space.

Let’s look at this from a different point of view. These days on social media we see big brands making a lot of effort to be more human and more personal in the online and digital space. They have teams of people who actively respond to complaints so that customers know they are dealing with a real person. They spend a lot of money on PR and marketing of their CSR efforts, their diversity and inclusion agendas, their various initiatives / activities to improve local community / society, and even their political stances where it makes sense for them to do that.

When that happens – do we see the brands as being less professional? Do we see them as being less credible?

Importantly – why are big brands trying to make the effort to be more human in the social space?

But, independent consultants (seemingly) struggle with sharing their personal stuff online. By personal stuff, I don’t mean family or friends stuff. I mean things like the big brands make big efforts to talk about:

  • What are your political beliefs?
  • What are your thoughts on LGBTQ+?
  • What are your thoughts on sexism?
  • What are your values?
  • How does any and all of this show up in the design of work you do?

These things matter. We don’t live in bubbles where these things are only private matters not to be shared with the world. That way of operating is long done with. Politicians and public figures take to the likes of Twitter to air their opinions about all these topics and more. We don’t live in an age where only if you’re a professional commentator are we allowed to hear your perspectives on life.

In my social network feed I have people – consultants – commentating on:

  • Menopause
  • Mental health
  • Day to day life
  • War
  • Politics
  • Family life
  • LGBTQ+ issues
  • Sexism

And I value each and every opinion in this vain. It lets me know what these individuals stand for. What they believe. Their posts help me to know if I think the same. If my own thinking needs to be challenged. It’s important because it lets me know if they’re the kind of person I want to create a longer lasting relationship/friendship with. Not because we might do business with one another in the future – but because they’ve made themselves more human.

It’s an interesting ongoing space to balance. I’m clearly advocating for more openness of opinion from consultants. But that’s not easy to do. Sometimes we may want to say something, but can’t find the words. Sometimes we have an opinion but fear what others might respond with. Sometimes we just don’t like the person and turn off from what say. Sometimes people struggle with the content because it triggers or provokes a visceral reaction. And there may be more besides.

As always, I’m interested in knowing your opinions. Either here on the blog, or over on Twitter or LinkedIn.


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 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.