Transcripts
Hey Megan, let's do a podcast. Great idea. What
Speaker:should we talk about?
Speaker:Today we're talking about the Human-Centered Adoption & Change
Speaker:section of the AI Implementation Canvas.
Speaker:Megan, how do we bring the people component to any AI
Speaker:project that we're implementing in a nice,
Speaker:organized way? Well, part of it is just
Speaker:having conversation, right? The whole point of the AI Implementation Canvas is there's
Speaker:14 different planning dimensions, 14 conversations we can be
Speaker:having around AI.
Speaker:And it's these conversations, people to people, that
Speaker:are really important as we make big decisions that affect our
Speaker:organizations, our performance, our people, our
Speaker:customers, our community. And that's one of the things
Speaker:that learning professionals do really well.
Speaker:We think about the people, and we also really
Speaker:rapidly onboard to a new topic; we focus on the performance of
Speaker:other people, we bring experts together, we facilitate conversations — we get things
Speaker:done. This now is
Speaker:not just a conversation, and we're not engaging just around building learning
Speaker:products. As we move into a more AI enabled world, I
Speaker:want to challenge us to broaden how we look at learning and performance
Speaker:in the organization, and bring in these other skill
Speaker:sets, and perhaps contribute in a different way. We
Speaker:can facilitate conversations around the Canvas. We can
Speaker:leverage our network within the organization to seek out the right stakeholders and bring
Speaker:people together to get things done. And we can leverage that
Speaker:unique perspective that we have as an advocate for the learner — or the
Speaker:worker, or the customer, or the community member, the constituent,
Speaker:the patient — in all of our conversations. So the
Speaker:conversations around the Canvas really are chunked into
Speaker:four sections. There's Strategic Foundations, Technology &
Speaker:Experience Infrastructure, Design & Implementation Enablers, and
Speaker:let's talk about Human-Centered Adoption & Change.
Speaker:AI is certainly going to be changing the way that people interact with
Speaker:each other, not just how they interact with AI, because
Speaker:we're adding this, kind of, this new dimension into the mix, right?
Speaker:We are. And yet as we add in this new
Speaker:dimension, this new teammate — sometimes it's referred to as another teammate
Speaker:you might hire and give performance coaching to. But
Speaker:I want to stack this on top of — in the
Speaker:last, now, six years — a move toward increased work
Speaker:from home, shorter job tenure, a
Speaker:lot of gig work, really a fragmentation of our
Speaker:social engagement in the world
Speaker:with social media algorithms, a
Speaker:fragmentation of the perspectives we get exposed to, and
Speaker:really be thinking about how do
Speaker:we maintain social engagement, human to
Speaker:human, across the organization and the benefits
Speaker:of that, that social engagement energy, that social construction
Speaker:of what our reality
Speaker:is and our processing of the world. How do we
Speaker:bring all those minds together, even though it's very,
Speaker:very easy to go and grab your laptop,
Speaker:work at home, not talk to anybody else and get a lot
Speaker:of stuff done.
Speaker:You mentioned "across the organization." And so I think
Speaker:many AI initiatives, you know, they're not just a single
Speaker:team; they're like going broad across
Speaker:an organization. And so there's got to of course be preparation
Speaker:and planning on how that needs to roll out. I
Speaker:would imagine that in the early days of AI that wasn't something we were thinking
Speaker:a whole lot about. It was more like, drop this in, see what happens.
Speaker:"Look, new cool tools!" But we need to have a conversation about that, right?
Speaker:Yeah. Our change professionals among us are going to be very, very
Speaker:important and continue to be important because there's more and more change. So as
Speaker:we think about how people process staggering amounts
Speaker:of change — not just at work, at home too, and in
Speaker:their communities — how do we support people? How do we
Speaker:give them a voice in the change, an ability to give feedback? How
Speaker:do we help them shift their thinking, their behavior,
Speaker:their workflow toward using these new
Speaker:tools and using those new tools effectively and productively?
Speaker:You asked the question of how do we support people? Well, of
Speaker:course that makes me think about your planning dimension of AI
Speaker:literacy and upskilling. Some organizations are
Speaker:embracing this opportunity and thinking very
Speaker:thoughtfully about how to train their workforce to use new AI tools. But
Speaker:this is a consideration that — everybody's thinking about it.
Speaker:Yeah. And it's interesting, right? So even in
Speaker:some organizations, they still haven't rolled out AI literacy training
Speaker:or AI tools. And yet for darn sure,
Speaker:many people, not everybody, but many people may be using AI tools or generative
Speaker:AI tools at home. They
Speaker:have this mismatch of technology
Speaker:environments from home to work. And how do we
Speaker:make sure that everybody is operating with
Speaker:basics of AI literacy? What is it? What's it good at? What's it not good
Speaker:at? It? What are the risks? What are the opportunities?
Speaker:A lot of times I see AI literacy training rolled out as a
Speaker:compliance activity. Our friends in
Speaker:compliance training are real good — make sure everybody gets something, it is
Speaker:consistent, you've all got it, we track it, we make sure you've got it.
Speaker:And that actually is, as much as
Speaker:I'm not always wild about a — you know,
Speaker:sometimes compliance feels like, "ugh, I gotta do my compliance training," right,
Speaker:or it comes as it feels heavy handed — they sure do know how to
Speaker:get things done. And then we get to proficiency,
Speaker:which is around "how can you use this tool well?" So there's the "what
Speaker:shouldn't you do?" "How does it work and what shouldn't you do?" And then "how
Speaker:do you, how can you use it well? How do you use it to improve
Speaker:your workflow and your work life?" And then we move
Speaker:from proficiency to fluency. How
Speaker:do we make AI part of the
Speaker:conversation? Not that we use AI for everything; in fact, how do
Speaker:we have smart conversations about when we do and don't use it, but how do
Speaker:we make that a normal part of the conversation? And those considerations are —
Speaker:they're both one-time
Speaker:considerations like "hey, everybody needs to do this." But then because the technology changes
Speaker:so frequently, it's worth circling back to it
Speaker:on a regular basis and make sure we update people's skills.
Speaker:When AI first came out, there was news
Speaker:articles and things that I was seeing about how
Speaker:there is maybe perhaps not the best
Speaker:fairness or there's bias sometimes built into the models.
Speaker:There's also some human protection issues
Speaker:when it comes to AI. So what do we need to think
Speaker:about when we think outside of our four walls of
Speaker:our organization? You know, this takes
Speaker:conversations around
Speaker:fairness, around inclusion, around equity,
Speaker:around social
Speaker:well being community wide, and
Speaker:levels it up and makes it that much more important. So I think what we
Speaker:can be thinking about here are all the same kinds of conversations that
Speaker:we've been having for the last decade
Speaker:applied in this new
Speaker:hyper-fast, hyper-complex environment
Speaker:around AI. So I want to include all those people who helped us make those
Speaker:decisions and choices before and keep them at
Speaker:the table, keep them as part of the conversation, and
Speaker:really be looking at all the dimensions,
Speaker:both our business, our employees, our
Speaker:customers, patients, students members, our community
Speaker:members and family members, as we start making
Speaker:big decisions based on some of this. And I
Speaker:kind of have this matrix right? The more
Speaker:impactful the decision and the
Speaker:faster the decision gets made — both of those
Speaker:are signals that say, "ah, we ought to like maybe add in
Speaker:some meaningful friction, some review, some human perspective
Speaker:on those as we go."
Speaker:One takeaway that I think I have here, as I'm thinking about everything
Speaker:we've talked about, is that when we
Speaker:introduce AI into our organizations, our systems —
Speaker:those are made up of people, and
Speaker:systems of people are inherently kind of complex systems.
Speaker:And so it's not
Speaker:just a very simple, straightforward "who's using it
Speaker:for what and where and when?" There's a lot of —
Speaker:it's a little bit of a web, and you have to think about how that
Speaker:introduction of something is going to kind of work its
Speaker:way out into the web, and one thing is going to pull and affect another
Speaker:thing. Kind of gets that ecosystem conversation we
Speaker:had last season, huh? Yeah. Cool. Cool.
Speaker:All right, Megan. I know you. One more thing. What have you got? You know,
Speaker:it's interesting. I have run a number of workshops
Speaker:around the Canvas as we aim to upskill learning
Speaker:professionals about AI implementation.
Speaker:And we intentionally save the Human-Centered Adoption & Change for
Speaker:the last part of the conversation, and it's always interesting
Speaker:because I was working with one group and they're like, "oh,
Speaker:this is where we feel comfortable now!" And
Speaker:the conversation we then had was, this
Speaker:is the conversation that people who might be comfortable in the other four quadrants
Speaker:are not comfortable having. This is a conversation we can lead.
Speaker:We may participate and ask questions in the other domains, but
Speaker:this is where we can play an active role. And
Speaker:so as comfortable as we feel here and as uncomfortable as
Speaker:we feel in the other three sections, we can have a little bit
Speaker:of empathy about our colleagues cross functionally,
Speaker:because they're feeling the same way, just about a different part of that
Speaker:Canvas.
Speaker:All right, Megan, how'd that go? This was fun.
Speaker:What I really liked, Meg, was the opportunity to wrap up this
Speaker:mini-series on the AI Implementation Canvas, and
Speaker:each — people, technology and people — we've said across
Speaker:each of these four that people show up in every one
Speaker:of the sections, but this is really the people section. Technology
Speaker:shows up in every one of the sections, and the
Speaker:interplay here is really, really important.
Speaker:This is Meg Fairchild and Megan Torrance, and this has
Speaker:been a podcast from TorranceLearning. Tangents is the
Speaker:official podcast of Torrance Learning. (As though we have an unofficial
Speaker:one.) Tangents is hosted by Meg Fairchild and Megan
Speaker:Torrance. It's produced by Dean Castile and Meg Fairchild,
Speaker:engineered and edited by Dean Castile, with original
Speaker:music also by Dean Castile. This episode was
Speaker:fact checked by Meg Fairchild.
