APS Blog

Do Values Matter

Wed, 25 Feb 2026 12:00:00 Z

It’s 07:36 on a crowded platform and it’s just been announced that all morning trains into the city have been cancelled due to a signalling issue. There’s a ripple of movement as hundreds of passengers react to the news.

We’ve all been in similar situations. Cancelled trains, missed buses, a car that won’t start. How do people tend to respond in those moments? Do they immediately email the office? Open journey apps, scanning for alternative transport? Pace up and down, venting their frustration aloud?

Sometimes we’re not alone when disruption hits. What happens when you’re in a group—colleagues, friends, family—and everyone responds differently? The planner clashes with the panicker. The joker annoys the worrier. The pragmatist tries to rally the team, while someone else just wants to be left alone. Individual reactions collide. Tensions surface. What started out as one shared problem sparks a series of relationship conflicts.

And it’s not just on train platforms or neighbourhood streets. The same thing happens in meeting rooms, in project kick-offs, during any moment of sudden change at work - A key client postpones. Budgets are unexpectedly cut. New regulations land overnight. The plan everyone agreed on yesterday is thrown up in the air. Any disruption triggers ripples of reactions.

So, what if it’s not the disruption itself that derails high-performing teams, but the clash of what each person is naturally inclined to protect, prove or prioritise? What’s really at play in these moments are individual values—what Hogan describe as “the interests, motives, and drivers that shape what a person strives to attain in life.” Values set the agenda for what each person feels urged to defend or restore during disruption. They’re often unconscious, internalised early and rarely spoken aloud, but they govern the decisions people make—whether to stand firm, compromise, seek harmony, or push forward.

What it can look like

A manager driven by Security pushes to pause all non-essential activity when budgets tighten. If colleagues who value Aesthetics see their work deprioritised without discussion, this could lead to frustration and a drop in visible creative energy.
As a commercial opportunity emerges, a leader motivated by Commerce lobbies for a fast pivot toward high-value clients. Others, focused on Altruism, might actively resist, citing values misalignment. The impasse becomes a flashpoint for previously unspoken tensions—and focus drifts from execution to internal disagreement.
In urgent discussions, someone with a strong Power drive makes rapid, unilateral calls. Team members who favour Affiliation or Hedonism could disengage, pulling back from the conversation and shifting concerns to private side channels rather than addressing them upfront.

If leaders don’t know what really drives them, or those around them, are they likely to explore ways to explain the driving forces behind their decisions? Will they be equipped to understand why some people applaud their behaviour, whilst others barely tolerate it? And what’s at stake if they don’t develop these skills? Hogan notes, “Misaligned values between organisations and leaders, organisations and teams, or organisations and individuals can all cause workplace conflict.” In practice, this means projects stall, talented people move on, and energy gets lost to workarounds or silent disengagement. The cost isn’t always visible in the moment, but shows up through missed opportunities, hard-to-explain turnover, and outcomes that don’t match the team’s real potential.

What might help?

If these situations resonate, here’s some strategies we’ve seen move the needle:

Share individual leader MVPI profiles 1:1: Bring hidden drivers into awareness; give leaders language for their own instincts and blind spots, supporting better decision accountability in high-pressure moments.
Share anonymised MVPI profiles with teams: Make underlying team dynamics discussable in the open, diffusing personal judgement and helping uncover where value clashes explain recurring friction or misfires.
Map MVPI profiles against future team needs in recruitment and succession decisions: Surface where current values coverage is robust—or missing—so you can avoid reinforcing blind spots, build intentional diversity of drivers, and make sure appointments align with strategic direction.

Reference
Robinson, E. (2024). The Importance of Values | Hogan Assessments. [online] Hogan Assessments. Available at: https://www.hoganassessments.com/blog/the-importance-of-values/.

The Future Is Here: AI, Personality, and the Impact

Wed, 01 Nov 2023 12:00:00 Z

Original post: Hogan Assessments

Before we start catastrophizing about our future AI rulers, we should stop and appreciate the potential good that artificial intelligence can offer. The impact of AI on personality assessment and workplace communication will likely be positive—and extensive.

Recently on The Science of Personality Live, cohosts Ryne Sherman, PhD, chief science officer, and Blake Loepp, PR manager, spoke with Michal Kosinski, PhD, associate professor in organizational behavior at Stanford University, about the evolving technology of artificial intelligence.

Michal’s primary research focus is studying humans in a digital environment using cutting-edge computational methods, artificial intelligence, and big data. He was also behind the first press article warning against Cambridge Analytica, the privacy risks they exploited, and the efficiency of the methods they use.

Let’s look at how AI language models have evolved, what AI-assisted communication might become, how AI affects the future of personality assessment, and whether AI language models can be creative.

The Evolution of AI-Language Models

Within the next few months (as of March 2023), AI language models will become exponentially more capable and ingenious. How does that explosive growth happen?

The approach to the development of AI language models started with chess. At first, software engineers and data scientists fed AI chess programs with archives of chess games played by humans. Then they equipped two AI programs with a virtual chessboard and instructions for how to play without any human intervention. “For the first few million games, those models were completely stupid,” Michal said, explaining that the rate of play was millions of games per second. “But soon, after a few hours, what emerged was this alien, superhuman software that could play chess at a level completely unachievable to human players.”

Software developers and artificial intelligence specialists used the same adaptive strategy to teach AI models how to craft language. Humans learn language through conversation, context, and correction. They make mistakes, learn, and make mistakes more rarely over time. “At some point they stop making mistakes and reach new levels of language. The same approach was used to train ChatGPT and similar models,” Michal said. The AI programs were given sentences with one word missing, failed millions of times to fill in the blank correctly, and then began to get it right. After a few million dollars of electricity and a few billion sentences, Michal quipped, the programs showed language mastery at an extraordinary level.

The AI revolution originated by teaching machines to solve problems using the same strategies that we use to teach humans: reinforcement and feedback. At first, the machines make obvious logical mistakes, but then they don’t. “The AI is responding to you as if as if it’s another person, which is the most incredible thing,” added Ryne. Because computers can exceed humans in logical ability, they are well suited to both playing chess and using language.

AI-Assisted Communication

“AI is a revolution comparable with the invention of written language,” Michal said. Manual writing gave humans the ability to communicate across time, sometimes thousands of years in the past. Knowing how to use a stylus, quill, or pencil was an essential method for communication before computers. Now, knowing how to use a keyboard is essential. Very shortly, the same fundamental change will happen with AI language models, Michal predicted.

“I think that GPT is potentially a new language for humanity to communicate at speed and convenience unheard of and impossible before,” Michal said.

An AI language model won’t just help humans write emails. It will craft the perfect message in the language that is most readily understood for the recipient. Here’s how.

Imagine that Michal wants to send Ryne an email. An AI language model knows and remembers all the events of each person’s life and has consumed every piece of digital communication each has produced. If Michal asked the AI to send a message to Ryne, he could make the request in very few words as if speaking to a good friend with intimate knowledge of him. But because the AI knew Ryne at that same level, it could “translate” Michal’s message into the perfect form for Ryne. The AI could use not only Ryne’s preferred language, such as English or Mandarin, but also a highly personalized form of that language unique to Ryne.

“In terms of the potential for translation, it knows the meaning of what you’re trying to say. It can translate that into a meaning that somebody else can understand in the way they understand,” Ryne said.

Another sense of AI-assisted communication is searching the internet. You wouldn’t ask the AI language model to find a website for you; you’d ask it the question you wanted to learn. It would search all websites and tailor its answer to any length or depth for your individual understanding of the world.

AI in Personality Assessment

Artificial intelligence is great at knowing and remembering what has been written, both words and data. For an AI language model to predict personality based on language, you’d need to first collect a lot of quality data. Michal pointed out that AI language models already understand language, of course, and can translate words into analyzable numbers. “They already understand psychological concepts like personality,” he said. These models have read texts written by introverts and extroverts and could theoretically detect, based on a fragment of a text, whether a person is introverted or extroverted.

Ryne imagined whether personality assessments of the future would have questionnaires and self-reporting. “One of the big questions surrounding this topic is to what degree I’m a willing participant in this endeavor,” he said. The quality of publicly available information versus data gained from individuals intentionally taking a personality assessment will differ substantially. The AI-assisted analysis would likely be higher quality in the latter case. Voluntary participation would also address questions of ethics.

Using big data models to predict personality characteristics is not a new notion. It has positives: it can analyze millions of people in a minute, and it can match people with compatible work or suggest workplace training and development. It also has negatives: it can be used to invade privacy or manipulate people. “As with many other technologies, we focus on the risks of the technology itself, completely forgetting that the real risk is in the intentions of the users,” Michal responded.

Artificial Intelligence and Creativity

A new fronter in AI language models is innovation and creativity. Humanity has taken generations to refine speech and writing. Individual humans spend over a decade learning to speak and write. AI language models have mastered written communication in a few years at a high level that continues to increase.

Michal compared AI creativity to human creativity in that most of us learn and combine elements of what we know or have experienced in new, creative ways. Perceiving computers as nothing but glorified calculators is short-sighted thinking, he said. That computers can incorporate and build elements into new results makes them fundamentally creative too.

“Many other animals are also creative in their own ways that we do not always recognize because it’s just not our type of art. The same applies to computers,” Michal said. “They learn from us, they learn from each other, and they become extremely creative with what they are good at—and they’re increasingly good at anything we ask them to do.”

Note: When ChatGPT (March 23 version) was asked to provide a quote in fewer than 120 characters about how it learned language, this was its response: “Words woven, sounds spoken, meanings grasped. A symphony of curiosity, immersion, and connection. Language learned, world unlocked.”

Listen to this conversation in full, and find the whole library of episodes at The Science of Personality.

HR’s Biggest Challenge: Succession Planning

Wed, 04 Jan 2023 12:00:00 Z

In the 1970s, only 8 percent of S&P 500 CEOs were recruited externally. That number grew to 22 percent in 2014. Yet, outsiders are almost 7 times more likely to be dismissed within a short tenure than homegrown CEOs. No matter how much a board learns about an outside candidate, executive stakeholders simply have a better understanding of an internal contender’s strengths and weaknesses, especially as they relate to the specifics of the current business landscape and strategic objectives. As a result of the inherent “information misalignment,” the chance of making a mistake is much higher for a CEO hired from outside the company.

Most stakeholders will admit that they know this already. But what they won’t admit is that the expressed need to bring in an outside CEO is evidence that neither the board, the current (or previous) CEO nor the chief of human resources successfully performed one of their most crucial, shared responsibilities: building a sustainable leadership pipeline that readies executives and potential executives to advance at all levels of the organisation.

There is good reason effective succession planning eludes so many otherwise functional companies. Making inferences about future performance, the variance of organisational politics and a tendency to devote limited (if any) focus to assessing “hidden potential” often hinder otherwise valiant efforts. For example, there are several reasons an individual may be nominated to participate in a succession plan, but far too often these individuals are identified because they are socially skilled, confident and interested in influencing others and moving up the corporate ladder. However, just because an individual is rewarding to deal with, doesn’t mean that the organisation should devote resources to his/her development.

When it comes to desired leadership outcomes, emergence does not necessarily equal effectiveness. If beating the competition remains the ultimate goal, an organisation’s leadership pipeline needs to be filled with those who can successfully lead high-performing teams. Accurately identifying top talent must involve science in the form of objective, relevant validated data. Despite guidance from the academic and business literature, some companies still base these important decisions on politically fraught processes or confound successful emergence with effective leadership. But clarity is not unattainable. According to various studies, successful managers tend to spend their time managing up by networking and politicking, whereas effective managers spend their time managing down by taking care of subordinates and driving team performance. Rarely do the two groups overlap.

What’s more, there is a common misunderstanding amongst most executives that all individuals considered for a succession plan should be able to effectively lead people, as opposed to advancing as a leader of processes or thought (i.e. subject matter expert), for example. Tech companies in the Fortune 100 have pioneered the notion that not everyone makes a great people leader. In addition to the typical “high potential” evaluation models, organizations like Microsoft and Cisco smartly consider other “leadership” skill sets that lend themselves to domains such as operational efficiency or innovation. In other words, insisting on professional people-leadership development for an individual who lacks the interest or compulsion to guide others toward stretch goals only sets up that valued employee for inevitable failure.

Well-validated personality assessments give a preview into which path forward is most conducive to an individual’s inherent behavioral patterns and latent interests. Those who have the proclivity to impose structure and the drive to keep things predictable will demonstrate behaviors conducive to process leadership. Those who have the propensity to seek inspirational ideas and who also emphasize the importance of imagination will likely have an easier time in a thought leadership role. And the working styles of those compelled to stay knowledgeably up-to-date as well as demand sound rationales to determine courses of action will be more conducive to data-dependent jobs. Having such information available in easy-to-understand terminology can help stakeholders vested in the organizational well-being leverage employees’ natural tendencies for more informed and specific succession planning.

Our business landscape continues to shift and evolve at an ever-faster rate. People represent the difference between an organization’s success and failure. The stakes of correctly identifying and developing the next generation of leaders could not be higher. Focusing on specific, differentiating options for advancement early in the careers of valued employees will only serve to benefit the organization. Basing the related evaluations of potential on objective data-driven metrics will help HR overcome the ultimate challenge: keeping the pipeline from entry level all the way to the CEO flush with options for filling vacancies.

This article originally appeared in Human Resource Executive.

When Personality Counts

Fri, 29 Mar 2019 00:00:00 Z

The debate about the usefulness of using personality tests in selection waxes and wanes.

Cynics and sceptics complain about consultant greed and test costs and others about the fact that people tend to lie on the tests. Supporters and apologists point to the costs of making bad decisions and the validity evidence of tests.

A central feature of the argument is about how much personality counts in explaining business success and failure. Robert Hogan in his book Personality and the Fate of Organisations makes a very strong case for the personality of leaders being extremely influential factors in business success and failure.

One of the oldest debates in psychology is called the person-situation debate. I investigated it for my PhD over 40 years ago. It is the question of the major determinants of behaviour: the sort of person you are, or the situation in which you find yourself.

In a brilliant paper in the Academy of Management Journal in 2015, Tim Judge and Cindy Zapata made some simple but important points about the role of personality at work. They suggested a dozen factors where personality makes all the difference

(1) The impact of decisions on coworkers/results, or “whether the decisions an employee makes impact the results of coworkers, clients, or the company”. Thus in some jobs (aviation inspector), the way they do the job (as a function of their personality) can make all the difference

(2) The consequences of error, or “how serious the results would be if the worker made a mistake that was not readily correctable”. Not so important for the librarian or language teacher, all important for the surgeon and ships captain.

(3) The responsibility for health/safety of others, or “the degree to which the employee is responsible for the health and safety of others”. Of little relevance to a proofreader but all important for a dentist or ambulance driver

(4) The unstructured (vs. structured) work, or “the extent to which the job allows the worker to determine tasks, priorities, and goals” (unstructured work) versus “the degree to which the job is structured for the worker” (structured work)

(5) The freedom to make decisions, defined as “the degree to which the job offers considerable decision-making freedom, without supervision”

(6) The variety, which refers to “the extent to which the job requires the employee to do many different things at work, using a variety of skills and talents” (low scores reflect little variety, high scores reflect significant variety).

(7) The independence in completing work, where “the job requires developing one’s own ways of doing things, guiding oneself with little or no supervision, and depending on oneself to get things done,” as opposed to working under a predetermined set of rules, under close supervision, or in dependency on others for guidance

(8) The attention to detail requirement, or “the extent to which the job requires being careful about detail and thoroughness in completing work tasks”

(9) The social skills requirement, defined as “the degree to which an occupation frequently involves working with, communicating with, and teaching people”

(10) The level of competition requirement, referring to “the extent to which the job requires the worker to compete or to be aware of competitive pressures”

(11) The innovation/creativity requirement, which is “the extent to which the job requires creativity and alternative thinking to develop new ideas for and answers to work-related problems”

(12) When dealing with unpleasant or angry people, or “how frequently employees have to deal with unpleasant, angry, or discourteous individuals”