Would They Tell You?

00:00:13: Hello and welcome to this week's reflection episode.

00:00:17: Let me start with a couple of questions.

00:00:20: If you are being asked, To give all your knowledge & insights to someone else And You aren't planning on giving up Your job What would you do?

00:00:28: You're seeing Someone younger and less expensive Who can Do what you do in half the time.

00:00:33: How does that make you feel A colleague under your responsibility?

00:00:38: Produces low quality work?

00:00:40: Does something potentially harmful to The company?

00:00:43: Would you report it or try to fix and hide?

00:00:46: Protecting ourselves in our positioning is typical human behavior.

00:00:51: We don't like give up on a position, or status which we earned in any kind of way especially not if was through hard work.

00:00:59: Now I could have asked the same questions And made them about AI instead.

00:01:03: another person.

00:01:05: The dynamics driving all behaviour stay mostly the same.

00:01:09: The fear being replaced by AI Is irrational response.

00:01:13: Over the past years, there have been enough AI-related layoffs and headlines predicting a job apocalypse.

00:01:20: People are seeing the productivity gains —and know the numbers game most companies are playing—so securing their own position already drives internal competition in politics at many companies... ...and its undermining collaboration and collective

00:01:35: learning.".

00:01:36: When people hide work-slop, mistakes & unethical A.I behavior It becomes another sign of a lack of leadership driving one the biggest disruptions to human work and life.

00:01:48: In the main episode on psychological safety, I argued that AI adoption doesn't just expose leadership weaknesses but amplifies them.

00:01:58: When decisions about how build connection between humans are made by people who don't get see daily works we need show what really drives results.

00:02:09: In many organizations, this doesn't happen.

00:02:12: The reporting is focused on metrics that cannot represent collaboration collective thinking and idea generation.

00:02:20: They don't show the human connection That can not be replaced by machines but holds significant value And what can't be measured isn't seen and not accounted for.

00:02:30: If people cannot talk about how they work with technology What's the value?

00:02:35: Where it falls short of producing any organizations will lose.

00:02:40: The lack of meaningful returns reported by many companies who heavily invested in fast AI adoption is just one cost.

00:02:49: Companies eventually loose trust and engagement from their human workforce, which brings productivity further down.

00:02:56: People who feel like a cog on the machine will either behave like one or leave to company that still values their work And the human connection that brings inspiration, motivation and new ideas goes right with them.

00:03:09: If performance is your key metric you'd better know what drives it!

00:03:13: The foundation to this knowledge is psychological safety In the main episode I presented Google as a company who understood the value of psychological safety.

00:03:23: They thrived on their people-centric open culture But they have changed.

00:03:28: When growth slowed down Their focus shifted towards bottom line.

00:03:32: They hired a Wall Street CFO and followed the financial market logic.

00:03:37: Sustainable long-term growth, as held up by founders Larry Page & Sergey Brin was replaced by shareholder Focus.

00:03:44: One of their first big layoffs was highly criticized for how it was executed.

00:03:49: People received their notices via email And were cut off from organization immediately.

00:03:55: That's opposite to an open and people centric culture.

00:03:58: It is kind signal that needs no further explanation.

00:04:02: The race is on and you have to fight to stay on it.

00:04:05: And this the reality for many workers today, not knowing what will happen in their jobs in the near future?

00:04:12: The question is if that kind of uncertainty would allow anyone really leverage the value of AI technology and manage their business in a sustainable way.

00:04:22: Navigating these uncertainties one important leadership responsibility.

00:04:27: right now Of course, no one can foresee the future and your work depends on the strategy of your company.

00:04:33: Your responsibility is to focus what's in your hands how you team works together.

00:04:38: The way they use technology Is just as much under your control & influence As openly talk about its limitations And it real value.

00:04:48: So let me give two practices and one principle To build and protect psychological safety and the second will be focused on AI adoption.

00:04:59: Consider first practice foundational.

00:05:02: It's about your own, in team reactions The moment someone takes a risk.

00:05:07: Let me explain what I mean by a RISK.

00:05:09: Someone admits mistake Has question that might sound stupid.

00:05:13: A TEAM member disagrees with you or someone else in the team Someone brings bad news Or simply says...I don't know.

00:05:21: Every one of these is small risks someone taking with YOU and others.

00:05:26: And in the half second after they take it, something happens.

00:05:51: If you and other team members show reactions that read like disapproval, blame or feel humiliating in any kind of way.

00:05:59: the message was sent before you said a word.

00:06:02: We all check what it costs us to speak up... ...and so does everyone else in the room.

00:06:07: People run these small tests all the time And they calibrate how much to risk next-time based on what comes back.

00:06:14: So the practice is to guard your reaction In the moment its being tested.

00:06:18: So for the next weeks, treat every one of those moments as a small assessment.

00:06:23: When someone admits mistake, disagrees raises question or concern notice first impulse check how you intend to act on it and stop if would make them regret doing that.

00:06:36: when somebody has questions notice whether your about making feel slow even asking.

00:06:43: If they bring bad news.

00:06:45: notice whether reaction is teaching to come to you sooner next time or keep it longer, entirely from you.

00:06:53: You won't get it right every time!

00:06:55: I still catch myself reacting before I've thought especially when i'm under pressure and think that already know the answer.

00:07:02: The practice requires continuous training.

00:07:05: It's notice moment for what is And repair it When you got wrong.

00:07:10: So how should handle your reaction?

00:07:13: Or someone in team wasn't helpful?

00:07:16: Address Don't hide it.

00:07:19: You can use the following recovery moves When The Bad Reaction was yours, the simplest is to name It and re-open the door.

00:07:28: I'm sorry this came across wrong.

00:07:31: If the moment has passed And you only realize that later go back To the person i've been thinking about our meeting.

00:07:38: i brush past what you raised?

00:07:40: And i shouldn't have.

00:07:41: Can we pick it up again going Back as a strong move because it tells people you are still Thinking About.

00:07:47: That's a signal that their contribution matters.

00:07:50: And when you're not sure whether your reaction landed badly, but you suspect it did just ask I think i might have cut you off on your concern.

00:07:59: Did it come across that way?

00:08:01: It gives people an opening without forcing anything.

00:08:06: Now When the bad reaction came from someone in the team The fastest repair is to put visible value back On what this person dismissed.

00:08:15: When someone has a question and gets eye-rolling, dismissive looks or sharp reply from a peer step in not to scold anyone but pick the question back up.

00:08:25: You don't have to call out their reactions – revaluing that contribution does work!

00:08:31: If this dismissal was rude or is continuous address behavior… But do it on the behaviour & NOT the person.

00:08:38: During meeting you can keep it lightly.

00:08:40: Let's Keep This A Place where any Question Is Fine To Ask.

00:08:45: Then, take the sharper conversation to one-to-one.

00:08:48: Also check on a person who was brushed off afterwards.

00:08:52: Say something like You raised something good and it got rough response.

00:08:57: I'm glad you said that.

00:08:58: Please continue.

00:08:59: do so.

00:09:00: Give them security.

00:09:01: what they asked is safe.

00:09:05: It's your responsibility to secure standard across team.

00:09:12: Especially now with AI, you will have people who pick up on using it faster than others.

00:09:18: Don't let them create a gap by diminishing other peoples' requests for clarification and the need for shared and continuous learning.

00:09:26: That was Practice One.

00:09:27: It's The Foundation.

00:09:28: Openly sharing mistakes that happen when people are working with AI is the second practice.

00:09:34: People need to feel safe to admit mistakes.

00:09:37: Everyone makes them And a leader doesn't talk about their own cannot ask others to do it.

00:09:43: We learn from mistakes, teams need collective learning and an environment where it is safe to address

00:09:48: failures.".

00:09:50: Similar to us treating the claims of highly confident people we easily follow the ultra-confident sounding AI output even when either can be confidently wrong –and how companies reward AI usage influences?

00:10:08: When they reward the fastest adopters and highest usage, The dashboard numbers go up.

00:10:13: And everyone looks more productive.

00:10:15: but mistakes will be part of outcome.

00:10:18: High usage isn't same as good usage.

00:10:21: As I mentioned in main episode a lot is fearful people protecting themselves Using tool because their scared not to and accepting whatever it gives them deliver results faster.

00:10:34: But we all know that quality and quantity aren't the same.

00:10:38: So don't reward someone who uses AI the most, but those who catch where it goes wrong.

00:10:44: What helps you and your team to stay critical about AI output is to run short weekly sessions that showcase AI mistakes.

00:10:52: Call them whatever you like!

00:10:54: One of teams I worked with named it AI Confession Session.

00:10:58: Invite everyone bring their case give them a structure so they bring value for entire team.

00:11:04: This can be equally good learning and fun.

00:11:07: Make sure to bring your own cases and start the sessions until everyone has gotten used it, then you can rotate.

00:11:14: The structure I would recommend is following – name a case and give short description of goal that you want achieve.

00:11:22: Next, briefly present the prompt in which other resources or input are used.

00:11:27: Then show result.

00:11:29: what caught attention to question.

00:11:31: next Present how you resolve mistake.

00:11:36: If you turn this into routine, it not only invites everyone to share their experience.

00:11:42: You also learn how your team is using AI over time and you start to see whether these use cases bring actual value.

00:11:50: The team also feels engaged to stay critical And catch mistakes instead of blindly accepting output.

00:11:57: Everyone will notice patterns in repeated mistakes which raises collective awareness And you leading.

00:12:03: this shows people that it's safe to share mistakes, That the tool is a tool and not replacement for critical thinking.

00:12:11: So those are two practices guarding your reaction to questions concerns, mistakes & problems... ...and catching mistakes working with AI openly.

00:12:22: Underneath both of them sits one principle What you do in service of two key responsibilities Making sure the reality of work reaches people who make decisions about it, and protecting the effectiveness of your team.

00:12:36: That's what psychological safety is for!

00:12:38: It's not about agreement comfort or everyone feeling good at work... ...it is about the work that needs to be done to build in maintain environments… …that allow for openness critical thinking learning collaboration.

00:12:52: if you protect this environment from your team will reach further than you can see.

00:12:57: The decisions about AI are mostly being made by people furthest from the work, and the only way that the truth reaches them is if the people closest to their work feel safe enough to address what works or doesn't.

00:13:11: And it can travel up from there!

00:13:13: So let me leave you with two more questions….

00:13:15: If People in your organization knew where AI adoption was going wrong and producing mistakes at Workslop instead of bringing value would they address this?

00:13:25: And would it reach the people who need to hear?

00:13:28: So take a close look at how your organization is working right now.

00:13:32: Speak with people, listen to critical voices and remember that not everything accounts for the value of human work gets measured!

00:13:42: That's all I have today.

00:13:43: If you enjoy this podcast do me a favor & leave review.

00:13:47: It tells others its worth their time.

00:13:50: The next episode will focus on what needs with the safety you've built.

00:13:56: And that's listening, with the intention to really understand.

00:14:00: So stay curious Stay tuned.

00:14:02: Thanks for tuning into The New Work Playbook Where work gets better because people matter.