{"title":"门槛上的领导力:生成式人工智能时代的意义、伦理和适应","authors":"Christine Haskell","doi":"10.1002/jls.70012","DOIUrl":null,"url":null,"abstract":"<p>We are living at a threshold moment, not because machines are getting smarter but because we are letting them rewrite the rules of what counts as smart. In under a decade, artificial intelligence (AI) has moved from a niche curiosity to an executive mandate, infiltrating how we draft policy, teach students, monitor performance, and even translate meaning itself. It doesn't just finish our sentences; it finishes our thoughts.</p><p>The deeper shift underway is not just technological. It is epistemological. Leadership today is not just about who sets the direction. It is about who gets to define reality. As generative AI takes up roles once considered deeply human (the explainer, the guide, the sense maker) the very core of leadership is up for grabs. Not by other humans, but by the tools we built and failed to govern.</p><p>We invent protocols that simulate character, but the harder work is to show up ourselves with character. That work cannot be outsourced.</p><p>What is needed now is not just new tools, but wiser stewards, leaders who know how to hold meaning open when machines try to close it. The current symposium authors embody that ethic. Through inquiry, critique, and care, they practice <i>Interpretive Stewardship</i>. Their work is not just timely; it is necessary.</p><p>That stewardship takes many forms, from cautious integration to principled refusal. Refusal is not withdrawal; it is deliberate boundary-setting around what must remain human. Both require the same discipline: resisting unexamined momentum, holding space for meaning, and choosing with care.</p><p>This issue of the <i>Leadership & Organization Development Journal</i> does not treat that shift as neutral. It treats it as contested. The scholars and practitioners in the symposium are not just watching history unfold; they are agents of it. They intervene with clarity and courage, insisting that leadership must be more than momentum, more than polished prompts, more than confidence without coherence. Their contributions—frameworks, case studies, provocations—reclaim leadership as an act of care, critique, and cultural memory.</p><p>What becomes of leadership when generative systems can perform their most human functions? This issue does not flinch. It does not appease. It resists the easy optimism of techno-utopianism with something more grounded: <i>interpretive stewardship</i>. Leadership as discernment under pressure. Leadership as refusal to drift. Leadership that stays human—not out of nostalgia, but out of necessity.</p><p>The essays that follow do not just analyze the problem. They <i>intervene</i> in it. To support such an inquiry, the contributions are organized into two thematic clusters:</p><p>Together, these two essays ask us to reconsider what leadership education is even for. If the goal is no longer mastery of content but discernment of context, we need new scaffolds for teaching students to resist the seduction of syntactic certainty. These authors model a different kind of leadership—<i>Interpretive Stewardship</i>. They do not just teach AI literacy; they model epistemic responsibility. What unites their work is not a shared methodology, but a shared stance: the willingness to question, resist, and reframe. They enact a form of interpretive stewardship, one that does not just absorb complexity but metabolizes it into ethical action.</p><p>The second cluster how we practice it in cross-pressured environments where cultural nuance, algorithmic logic, and human ethics collide. These essays show that interpretive stewardship is not just an educational imperative, but an applied leadership stance.</p><p>At the center is <i>“Nested Complexity: Leadership Across Human-AI Systems”</i> (Goryunova), a theoretical scaffold that integrates complexity science, organizational theory, and moral discernment. It identifies the interpretive layers—human, institutional, and algorithmic—that leaders must navigate. It highlights the paradoxes that define our time: speed versus deliberation, efficiency versus empathy, consistency versus discretion.</p><p><i>“Relational Leadership in the Age of AI”</i> (Kaan) takes that scaffold and makes it personal. Kaan critiques how AI-powered training platforms flatten cultural nuance and relational ethics. His relational-AI pedagogy is not just a critique; it is a reclamation. A call to return mentorship, context, and cultural fluency to the center of leadership development.</p><p><i>“Cross-Cultural Differences in AI Acceptance”</i> (Strandt) brings the empirical heat. Through a multi-country comparative study, Strandt shows that AI is never culturally neutral. How we adopt it and what we tolerate from it depends on deeper social scripts. This is not just interesting; it is urgent.</p><p>Together, these three essays form the architecture of this issue's deeper claim: that leadership in the age of AI is fundamentally interpretive. Interpretation, in turn, is shaped by complexity, culture, and constraints.</p><p>These papers are published against a backdrop of performative risk-taking, techno-theater, and epistemic drift. “Techno-utopians” proclaim their bravery as if “being willing to take the risk” is itself a credential, while sidestepping the responsibility that comes with impact. Regulation is framed as unhip, careful thought is dismissed as drag, and leadership is equated with momentum. We live in a climate that prizes performance over reflection—where power performs expertise, and those who challenge epistemic overreach, from women scholars to high-profile critics like Gary Marcus, are told they’re rude, too dark, or depressing, while complexity is waved away as an inconvenience.</p><p>The papers in this issue push back. They reassert that discernment is not an elitist view from an ivory tower, that care is not weakness, and that slow thinking and deep consideration are not obstruction. They are where the <i>craft of leadership</i> begins.</p><p>Across wildly different methods, domains, and styles, five papers converge on one shared insight: Leadership is no longer about answers. It is about holding the right questions open, especially when AI tempts us to close them too fast.</p><p>The symposium contributors exemplify a quiet but radical form of leadership. They hold the line between insight and overreach, speed and discernment, and convenience and care. They ask what meaning means before automating it. They defend ambiguity not as indecision, but as the ethical space where responsibility lives. In a world eager for answers, they offer the rare discipline of holding questions wisely—a shared ethic of stewardship over spectacle, discernment over drift.</p><p>As algorithms learn to anticipate our needs, simulate our tone, and rewrite our memory, leadership cannot just be about influence alone. It has to become a form of stewardship—of meaning, of boundaries, of human dignity. Against our deepest yearning, we cannot automate our way out of these times.</p><p>We cannot protocol our way into character. This is not a lament; it is a call.</p><p>Leadership is not vanishing; it is being rewritten. This threshold demands more than presence. It demands authorship.</p><p>Leadership, if stewarded wisely, can still carry us across.</p><p>None.</p>","PeriodicalId":45503,"journal":{"name":"Journal of Leadership Studies","volume":"19 2","pages":""},"PeriodicalIF":0.6000,"publicationDate":"2025-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jls.70012","citationCount":"0","resultStr":"{\"title\":\"Leadership at the Threshold: Meaning, Ethics, and Adaptation in the Age of Generative AI\",\"authors\":\"Christine Haskell\",\"doi\":\"10.1002/jls.70012\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>We are living at a threshold moment, not because machines are getting smarter but because we are letting them rewrite the rules of what counts as smart. In under a decade, artificial intelligence (AI) has moved from a niche curiosity to an executive mandate, infiltrating how we draft policy, teach students, monitor performance, and even translate meaning itself. It doesn't just finish our sentences; it finishes our thoughts.</p><p>The deeper shift underway is not just technological. It is epistemological. Leadership today is not just about who sets the direction. It is about who gets to define reality. As generative AI takes up roles once considered deeply human (the explainer, the guide, the sense maker) the very core of leadership is up for grabs. Not by other humans, but by the tools we built and failed to govern.</p><p>We invent protocols that simulate character, but the harder work is to show up ourselves with character. That work cannot be outsourced.</p><p>What is needed now is not just new tools, but wiser stewards, leaders who know how to hold meaning open when machines try to close it. The current symposium authors embody that ethic. Through inquiry, critique, and care, they practice <i>Interpretive Stewardship</i>. Their work is not just timely; it is necessary.</p><p>That stewardship takes many forms, from cautious integration to principled refusal. Refusal is not withdrawal; it is deliberate boundary-setting around what must remain human. Both require the same discipline: resisting unexamined momentum, holding space for meaning, and choosing with care.</p><p>This issue of the <i>Leadership & Organization Development Journal</i> does not treat that shift as neutral. It treats it as contested. The scholars and practitioners in the symposium are not just watching history unfold; they are agents of it. They intervene with clarity and courage, insisting that leadership must be more than momentum, more than polished prompts, more than confidence without coherence. Their contributions—frameworks, case studies, provocations—reclaim leadership as an act of care, critique, and cultural memory.</p><p>What becomes of leadership when generative systems can perform their most human functions? This issue does not flinch. It does not appease. It resists the easy optimism of techno-utopianism with something more grounded: <i>interpretive stewardship</i>. Leadership as discernment under pressure. Leadership as refusal to drift. Leadership that stays human—not out of nostalgia, but out of necessity.</p><p>The essays that follow do not just analyze the problem. They <i>intervene</i> in it. To support such an inquiry, the contributions are organized into two thematic clusters:</p><p>Together, these two essays ask us to reconsider what leadership education is even for. If the goal is no longer mastery of content but discernment of context, we need new scaffolds for teaching students to resist the seduction of syntactic certainty. These authors model a different kind of leadership—<i>Interpretive Stewardship</i>. They do not just teach AI literacy; they model epistemic responsibility. What unites their work is not a shared methodology, but a shared stance: the willingness to question, resist, and reframe. They enact a form of interpretive stewardship, one that does not just absorb complexity but metabolizes it into ethical action.</p><p>The second cluster how we practice it in cross-pressured environments where cultural nuance, algorithmic logic, and human ethics collide. These essays show that interpretive stewardship is not just an educational imperative, but an applied leadership stance.</p><p>At the center is <i>“Nested Complexity: Leadership Across Human-AI Systems”</i> (Goryunova), a theoretical scaffold that integrates complexity science, organizational theory, and moral discernment. It identifies the interpretive layers—human, institutional, and algorithmic—that leaders must navigate. It highlights the paradoxes that define our time: speed versus deliberation, efficiency versus empathy, consistency versus discretion.</p><p><i>“Relational Leadership in the Age of AI”</i> (Kaan) takes that scaffold and makes it personal. Kaan critiques how AI-powered training platforms flatten cultural nuance and relational ethics. His relational-AI pedagogy is not just a critique; it is a reclamation. A call to return mentorship, context, and cultural fluency to the center of leadership development.</p><p><i>“Cross-Cultural Differences in AI Acceptance”</i> (Strandt) brings the empirical heat. Through a multi-country comparative study, Strandt shows that AI is never culturally neutral. How we adopt it and what we tolerate from it depends on deeper social scripts. This is not just interesting; it is urgent.</p><p>Together, these three essays form the architecture of this issue's deeper claim: that leadership in the age of AI is fundamentally interpretive. Interpretation, in turn, is shaped by complexity, culture, and constraints.</p><p>These papers are published against a backdrop of performative risk-taking, techno-theater, and epistemic drift. “Techno-utopians” proclaim their bravery as if “being willing to take the risk” is itself a credential, while sidestepping the responsibility that comes with impact. Regulation is framed as unhip, careful thought is dismissed as drag, and leadership is equated with momentum. We live in a climate that prizes performance over reflection—where power performs expertise, and those who challenge epistemic overreach, from women scholars to high-profile critics like Gary Marcus, are told they’re rude, too dark, or depressing, while complexity is waved away as an inconvenience.</p><p>The papers in this issue push back. They reassert that discernment is not an elitist view from an ivory tower, that care is not weakness, and that slow thinking and deep consideration are not obstruction. They are where the <i>craft of leadership</i> begins.</p><p>Across wildly different methods, domains, and styles, five papers converge on one shared insight: Leadership is no longer about answers. It is about holding the right questions open, especially when AI tempts us to close them too fast.</p><p>The symposium contributors exemplify a quiet but radical form of leadership. They hold the line between insight and overreach, speed and discernment, and convenience and care. They ask what meaning means before automating it. They defend ambiguity not as indecision, but as the ethical space where responsibility lives. In a world eager for answers, they offer the rare discipline of holding questions wisely—a shared ethic of stewardship over spectacle, discernment over drift.</p><p>As algorithms learn to anticipate our needs, simulate our tone, and rewrite our memory, leadership cannot just be about influence alone. 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Leadership at the Threshold: Meaning, Ethics, and Adaptation in the Age of Generative AI
We are living at a threshold moment, not because machines are getting smarter but because we are letting them rewrite the rules of what counts as smart. In under a decade, artificial intelligence (AI) has moved from a niche curiosity to an executive mandate, infiltrating how we draft policy, teach students, monitor performance, and even translate meaning itself. It doesn't just finish our sentences; it finishes our thoughts.
The deeper shift underway is not just technological. It is epistemological. Leadership today is not just about who sets the direction. It is about who gets to define reality. As generative AI takes up roles once considered deeply human (the explainer, the guide, the sense maker) the very core of leadership is up for grabs. Not by other humans, but by the tools we built and failed to govern.
We invent protocols that simulate character, but the harder work is to show up ourselves with character. That work cannot be outsourced.
What is needed now is not just new tools, but wiser stewards, leaders who know how to hold meaning open when machines try to close it. The current symposium authors embody that ethic. Through inquiry, critique, and care, they practice Interpretive Stewardship. Their work is not just timely; it is necessary.
That stewardship takes many forms, from cautious integration to principled refusal. Refusal is not withdrawal; it is deliberate boundary-setting around what must remain human. Both require the same discipline: resisting unexamined momentum, holding space for meaning, and choosing with care.
This issue of the Leadership & Organization Development Journal does not treat that shift as neutral. It treats it as contested. The scholars and practitioners in the symposium are not just watching history unfold; they are agents of it. They intervene with clarity and courage, insisting that leadership must be more than momentum, more than polished prompts, more than confidence without coherence. Their contributions—frameworks, case studies, provocations—reclaim leadership as an act of care, critique, and cultural memory.
What becomes of leadership when generative systems can perform their most human functions? This issue does not flinch. It does not appease. It resists the easy optimism of techno-utopianism with something more grounded: interpretive stewardship. Leadership as discernment under pressure. Leadership as refusal to drift. Leadership that stays human—not out of nostalgia, but out of necessity.
The essays that follow do not just analyze the problem. They intervene in it. To support such an inquiry, the contributions are organized into two thematic clusters:
Together, these two essays ask us to reconsider what leadership education is even for. If the goal is no longer mastery of content but discernment of context, we need new scaffolds for teaching students to resist the seduction of syntactic certainty. These authors model a different kind of leadership—Interpretive Stewardship. They do not just teach AI literacy; they model epistemic responsibility. What unites their work is not a shared methodology, but a shared stance: the willingness to question, resist, and reframe. They enact a form of interpretive stewardship, one that does not just absorb complexity but metabolizes it into ethical action.
The second cluster how we practice it in cross-pressured environments where cultural nuance, algorithmic logic, and human ethics collide. These essays show that interpretive stewardship is not just an educational imperative, but an applied leadership stance.
At the center is “Nested Complexity: Leadership Across Human-AI Systems” (Goryunova), a theoretical scaffold that integrates complexity science, organizational theory, and moral discernment. It identifies the interpretive layers—human, institutional, and algorithmic—that leaders must navigate. It highlights the paradoxes that define our time: speed versus deliberation, efficiency versus empathy, consistency versus discretion.
“Relational Leadership in the Age of AI” (Kaan) takes that scaffold and makes it personal. Kaan critiques how AI-powered training platforms flatten cultural nuance and relational ethics. His relational-AI pedagogy is not just a critique; it is a reclamation. A call to return mentorship, context, and cultural fluency to the center of leadership development.
“Cross-Cultural Differences in AI Acceptance” (Strandt) brings the empirical heat. Through a multi-country comparative study, Strandt shows that AI is never culturally neutral. How we adopt it and what we tolerate from it depends on deeper social scripts. This is not just interesting; it is urgent.
Together, these three essays form the architecture of this issue's deeper claim: that leadership in the age of AI is fundamentally interpretive. Interpretation, in turn, is shaped by complexity, culture, and constraints.
These papers are published against a backdrop of performative risk-taking, techno-theater, and epistemic drift. “Techno-utopians” proclaim their bravery as if “being willing to take the risk” is itself a credential, while sidestepping the responsibility that comes with impact. Regulation is framed as unhip, careful thought is dismissed as drag, and leadership is equated with momentum. We live in a climate that prizes performance over reflection—where power performs expertise, and those who challenge epistemic overreach, from women scholars to high-profile critics like Gary Marcus, are told they’re rude, too dark, or depressing, while complexity is waved away as an inconvenience.
The papers in this issue push back. They reassert that discernment is not an elitist view from an ivory tower, that care is not weakness, and that slow thinking and deep consideration are not obstruction. They are where the craft of leadership begins.
Across wildly different methods, domains, and styles, five papers converge on one shared insight: Leadership is no longer about answers. It is about holding the right questions open, especially when AI tempts us to close them too fast.
The symposium contributors exemplify a quiet but radical form of leadership. They hold the line between insight and overreach, speed and discernment, and convenience and care. They ask what meaning means before automating it. They defend ambiguity not as indecision, but as the ethical space where responsibility lives. In a world eager for answers, they offer the rare discipline of holding questions wisely—a shared ethic of stewardship over spectacle, discernment over drift.
As algorithms learn to anticipate our needs, simulate our tone, and rewrite our memory, leadership cannot just be about influence alone. It has to become a form of stewardship—of meaning, of boundaries, of human dignity. Against our deepest yearning, we cannot automate our way out of these times.
We cannot protocol our way into character. This is not a lament; it is a call.
Leadership is not vanishing; it is being rewritten. This threshold demands more than presence. It demands authorship.
Leadership, if stewarded wisely, can still carry us across.