People ultimately choose to be motivated — when to give their best, go the extra mile, and offer radical ideas. The only thing leaders can do is shape the conditions under which others do, or don’t, choose to be motivated. Unfortunately, too few managers understand this, and so there is a gap between managers’ efforts and the results they’re getting. Three of the most offensive forms of “motivating” — drive-by praise, making stuff up, and guilt gratitude — can actually make employees feel less appreciated and erode their trust in a leader. The common shortfall among these approaches is that they all serve the leader giving the praise, not the recipient. If you want to direct your good intentions into more-meaningful expressions of recognition, consider these alternatives: Ask your employee how they accomplished their goal, explain how their efforts are contributing to the broader organization, and acknowledge the challenges they overcame to make such a valuable contribution.
To Anyone Who Thinks They're Falling Behind In Life
You don't need more motivation. You don't need to be inspired to action. You don't need to read any more lists and posts about how you're not doing enough. There's a magic beyond us that works in ways we can't understand.
Are Large Language Models Sensitive to the Motives Behind Communication?
Human communication is $\textit{motivated}$: people speak, write, and create content with a particular communicative intent in mind. As a result, information that large language models (LLMs) and AI agents process is inherently framed by humans' intentions and incentives. People are adept at navigating such nuanced information: we routinely identify benevolent or self-serving motives in order to decide what statements to trust. For LLMs to be effective in the real world, they too must critically evaluate content by factoring in the motivations of the source---for instance, weighing the credibility of claims made in a sales pitch. In this paper, we undertake a comprehensive study of whether LLMs have this capacity for $\textit{motivational vigilance}$. We first employ controlled experiments from cognitive science to verify that LLMs' behavior is consistent with rational models of learning from motivated testimony, and find they successfully discount information from biased sources in a human-like manner. We then extend our evaluation to sponsored online adverts, a more naturalistic reflection of LLM agents' information ecosystems. In these settings, we find that LLMs' inferences do not track the rational models' predictions nearly as closely---partly due to additional information that distracts them from vigilance-relevant considerations. However, a simple steering intervention that boosts the salience of intentions and incentives substantially increases the correspondence between LLMs and the rational model. These results suggest that LLMs possess a basic sensitivity to the motivations of others, but generalizing to novel real-world settings will require further improvements to these models.
The Feedback Fallacy
For years managers have been encouraged to candidly praise and criticize just about everything workers do. But it turns out that feedback does not help employees thrive. First, research shows that people can’t reliably rate the performance of others: More than 50% of your rating of someone reflects your characteristics, not hers. Second, neuroscience reveals that criticism provokes the brain’s “fight or flight” response and inhibits learning. Last, excellence looks different for each individual, so it can’t be defined in advance and transferred from one person to another. It’s also not the opposite of failure. Managers will never produce great performance by identifying what they think is failure and telling people how to correct it. Instead, when managers see a great outcome, they should turn to the person who created it, say, “Yes! That!,” and share their impression of why it was a success. Neuroscience shows that we grow most when people focus on our strengths. Learning rests on our grasp of what we’re doing well, not what we’re doing poorly, and certainly not on someone else’s sense of what we’re doing poorly.
Some Thoughts About Work
I think there are three things that can make work rewarding: working with cool people, working on cool things, and working in cool ways.
Properly Valuing Contributions
A major part of our mission as a company is to empower people. So naturally, at Qbix, we give a lot of thought to the best ways of doing that. This post describes a compensation model that we have designed, which clearly rewards people for their contributions, and actually drives everyone to compete
Don't soften feedback.
When I talk about balancing being directive and empowering as a leader, the distinction between being kind and being nice often comes up.
Paging Charity? How do I get my leaders to stop running teams Into the ground? - Stack Overflow
I'm a senior staff engineer, and I’m wondering what advice you might have for a person in my role in a large company to affect priorities and the speed at which work is "expected" to be executed.
Giving Altruism a Bad Name
Effective Altruism’s metrics-driven model of philanthropy is elitist, condescending and — most damning of all — extremely ineffective.
Framing charitable donations as exceptional expenses increases giving.
On what matters
This post was originally published in Sharetribe’s internal communication channel. I wrote it to describe to the team what motivates me in…
Self-Control and Optimal Goals: A Theoretical Analysis
Consumers set goals to achieve a variety of objectives such as losing weight, saving for retirement, and achieving better health. A large body of literature in psychology and consumer behavior shows that goals can help consumers achieve these objectives. However, there is almost no research that examines how we should set optimal goals. The purpose of this paper is to develop a parsimonious framework that examines how goals can help performance and how we should set optimal goals. We use the literature on hyperbolic discounting to model these issues. Our results show that goals can often increase performance but can also sometimes encourage procrastination. We show that some goals are worse than having no goals, even when the goals are achieved and the consumer exerts more effort because of the goal. We also find that the presence of goals can lead to myopic consumers behaving as if they were hyperopic. Our results also show that the most difficult goals should be assigned to consumers with moderate levels of motivation and self-control problems. We also find that it is sometimes optimal to set goals that are never achieved.
Research – Open Heart Mind
We’re developing Metavaluation — a participatory framework for recognising and rewarding the value of diverse contributions, from creative work and care to logistics and leadership.
Leadership: Values
A question I get quite frequently is “What makes a good leader?” One of the most important aspects of a good leader is that they have values. This may at first sound noncontroversial, but we are surrounded today by leaders who do not have values or whose only values are to get rich personally or to be powerful (or both). Tech investors have been especially guilty of enabling charismatic leaders, and sometimes even non-charismatic but wildly successful ones, who are fundamentally hollow and wi...
AI-Generated “Workslop” Is Destroying Productivity
Despite a surge in generative AI use across workplaces, most companies are seeing little measurable ROI. One possible reason is because AI tools are being used to produce “workslop”—content that appears polished but lacks real substance, offloading cognitive labor onto coworkers. Research from BetterUp Labs and Stanford found that 41% of workers have encountered such AI-generated output, costing nearly two hours of rework per instance and creating downstream productivity, trust, and collaboration issues. Leaders need to consider how they may be encouraging indiscriminate organizational mandates and offering too little guidance on quality standards. To counteract workslop, leaders should model purposeful AI use, establish clear norms, and encourage a “pilot mindset” that combines high agency with optimism—promoting AI as a collaborative tool, not a shortcut.
Refusing to Be the Victim – How to Adopt a “Player” Mindset at Work
You can’t expect others to fix your problems. When you take responsibility for making the best of any situation, you have the power to make things better.
