Cultural Strategist & Digital Transformation Advisor | Human-Centered Tech Leadership | Consumer Culture Scholar
Chicago, IL
Joined May 2007
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#strategicthinking: Brand Governments
My #SXSW Session "Future of Power: Bit Nations & Brand Governments" is up for public vote. Wld appreciate if you can support it by logging in to #panelpicker & VOTE UP! Thank you! #SXSW2020 #bigtech #branding #brand
panelpicker.sxsw.com/vote/10…
A little wit. A little intellectual mischief. Much needed intolerance for intellectual laziness, performative expertise, and AI-generated 'wisdom.'
A healthy dose of antidote. #UnapologeticallyHuman 😇
dr behice ece ilhan retweeted
El MIT ha presentado un informe histórico, que suscribo, elaborado por su Comité Ad Hoc, sobre el uso de la IA en la enseñanza, el aprendizaje y la formación en investigación, en el que propone una reorganización profunda de su modelo académico/educativo ante el avance de la IA generativa, entre lo que destaca, entre muchos otros aspectos:
– Diseño inverso (Backward Design): Se insta a los profesores a definir primero qué deben saber, comprender y valorar los estudiantes, para luego decidir en qué puntos específicos la IA suma o resta al aprendizaje.
– Enfoque de aumento, no de automatización: La meta no es prohibir la IA, sino rediseñar los programas y cursos para que la tecnología apoye el pensamiento crítico sin permitir la rendición cognitiva (cuando los estudiantes recurren a la IA antes de intentar resolver por sí mismos un problema difícil).
– Nuevos métodos de evaluación: Se desaconseja el uso de detectores de IA, por considerarlos poco fiables y propensos a generar desconfianza. En su lugar, se propone un mayor uso de exámenes orales, evaluación continua, proyectos prácticos, portafolios con revisiones presenciales y componentes sociales en cada área temática.
El informe propone 8 principios medulares para guiar la integración de la IA generativa en la educación superior:
· Sé humilde (Be humble): Reconocer que el ritmo del cambio tecnológico es demasiado rápido como para establecer reglas permanentes, lo que requiere flexibilidad constante.
· Sé audaz (Be bold): Afrontar la situación de forma proactiva mediante el rediseño profundo de los planes de estudio, en lugar de aplicar parches defensivos.
· Pon a la humanidad en el centro (Put humanity front and center): Priorizar las relaciones interpersonales, el florecimiento humano y el valor de la educación residencial (de humanos enseñando a humanos).
· Sumérgete en el aprendizaje / Preserva el esfuerzo constructivo (Lean into learning): Entender que el esfuerzo cognitivo y la dificultad son esenciales para aprender; obtener una respuesta rápida de una IA no equivale a adquirir conocimiento.
· Enseña con intencionalidad (Teach with intentionality): Diseñar las clases con propósitos claros, evitando tanto las prohibiciones reflexivas como los mandatos ciegos de la IA.
· No hay una solución única para todos (No one size fits all): El nivel de formación importa; una política o herramienta adecuada para un doctorando puede resultar perjudicial para un alumno de primer año que aún está construyendo sus bases conceptuales.
· Aumentación, no automatización (Augmentation, not automation): Utilizar la IA para elevar el nivel de los problemas que un estudiante puede resolver (potenciar el pensamiento), en lugar de delegar por completo la capacidad humana de pensar.
· Piensa más allá del aula y del campus (Think beyond the classroom and the campus): Considerar el impacto de la IA en el desarrollo integral de los estudiantes como personas y ciudadanos en el mundo exterior.
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I was already easily underwhelmed by prevalent, mediocre ideas. As if that weren't enough, now we have AI-amplified mediocrity produced by those very same mediocre ideas.🙄 The mediocrity is feeling like an Inception movie. something that we keep falling deeper and deeper into.
Being exposed to information ≠ understanding.
Understanding ≠ learning.
Learning ≠ Mastering.
But sure, let's keep confusing access to knowledge or intelligence with expertise. 🙄
The most ‘valuable’ or inevitable constituency to the system is the one w/ the conviction & courage to punish the system that don’t align with them. #Midterms2026
Customer Lifetime Value #CLV is a core customer strategy KPI, measured by recency, lifespan, frequency etc
#Election2024 reveals a new metric: Power to Punish
The most valuable constituency is the one w/ the conviction & courage to punish the leaders that don’t align with them.
dr behice ece ilhan retweeted
If you work at McKinsey, Bain, BCG, Accenture, EY, Deloitte, PwC, if you are an in-house consultant or an independent, you are witnessing the consulting industry being split in two.
I just mapped 60 core consulting skills (both hard and soft) against the impending threat of Generative AI.
The result is what I called the Consulting AI Threat Matrix, and it reveals which skills will be commoditized and which will become your ultimate competitive moat.
I plotted these skills across two dimensions (because I'm a consultant and I love a good quadrant 😅)
The dimensions are:
1) Modality of execution (Algorithmic vs. Interpersonal)
2) Environmental entropy (Deterministic vs. Ambiguous)
The findings are a wake-up call for how firms train their talent:
- The Commoditization Zone (Bottom-Left): Standard financial modeling, UI/UX, RPA, and slide generation are facing severe disruption. If your value is tied to synthesizing clean data in predictable environments, GenAI will do it faster.
- The Augmentation Zone (Bottom-Right): Cloud architecture, predictive modeling, and hypothesis-driven problem-solving. GenAI is your co-pilot here, but human knowledge and judgment is required to navigate the ambiguity.
- The Strategic Premium (Top-Right): Consensus building, crisis de-escalation, unbiased judgment, and executive storytelling. GenAI cannot read a hostile stakeholder or mediate a turf war between a CIO and a CMO. This is the human moat.
If you are a senior consultant, a manager, director, partner, or aspiring consultant, your career trajectory depends on migrating to the top right.
I put together a detailed 10-page paper breaking down exactly how these 60 skills were evaluated, the criteria for each quadrant, and how consulting firms need to restructure their training programs to survive this shift, plus what actions you can take to safeguard yourself.
Just ping me somehow (comment here or DM me) and I'll send you the paper.
All the best!
dr behice ece ilhan retweeted
🚨Out now in PNAS! The first ever (we believe) large scale RCT + field experiment on the performance effects of AI Personalization!
🚩 In a preregistered randomized experiment,
🚩 We paired 1,258 participants with AI agents prompted to exhibit varying levels of the Big Five personality traits.
🚩 These human–AI teams produced 7,266 display ads, evaluated by 1,168 human raters, and a field experiment on X with ~5M impressions.
I don’t need an AI detector. I know what expertise it takes to write a particular sentence and whether a student or a colleague has it.
That judgment is itself expertise.
Everybody is a thought leader….Until they have to articulate a coherent, competent POV in front of a crowd… without AI’s help. 😏🙄
Sit in a #datastrategy class and you start to see why tech fails. The conversation is often so divorced from behavior.
We need to constantly remember that there’s human and human system behind every data point. When that gets abstracted away, the gap brings failure.
Most enterprise problems are not capability gaps.
When tradeoffs remain unowned,
organizations keep building capability instead of making decisions. #Strategy #AIStrategy #CSO
Most enterprise problems are not capability gaps.
They are tradeoffs left unowned long enough to look like capability gaps. #Strategy #CSO #AIStrategy
Most enterprise problems are not capability gaps.
The tradeoffs are visible.
Ownership is not. #strategy #CSO #AIStrategy
Most enterprise problems are not capability gaps.
They are unowned tradeoffs. #strategy #CSO #AIstrategy
This is the most fertile structural moment for a credible #thirdparty opportunity in the US political market in years.
Not because ideology shifted overnight.
But because the rivalry structure loosened. #politics #politicalmarketing
