What are the core components of talent? V7

 What is the purpose of this article?

Enable founders, the C-Suite, board of directors, investors, and others to discuss the company’s talent requirements.

This article does not provide tax, legal or financial advice.

You must do your own research and fact-based analysis using current and relevant information.

AI did not write this article.  100% human written.

You can download a PDF of this article from: What are the core components of talent V7

How do you read this article?

• The body of the article contains description of the 10 core components of talent.
• The appendix describes the core skills that will be even more important in 2030 than 2025. The appendix is based on a report from the World Economic Forum. The value of future skills is illustrated using the board of directors.

 What are the critical learnings in this article?

• There are 10 core components of talent.
• People often focus on just 1 component of talent: Crystallized intelligence (e.g. historical skills, knowledge, experience, etc.) and ignore the other 9. This often leads to major problems, because historical skills, knowledge, and experience are quickly becoming obsolete.
• The core components of talent fit into the qualification’s sections of a typical job description.
• The core components of talent fit into the key competencies section of a typical job scorecard.
• An AI worker would have both a job description and a job scorecard.
• If AI is assisting a person in a role, then need clarity on how the AI’s 10 core components of talent are improving the person’s job scorecard.
• What is the definition of an AI worker? What is the definition of an AI agent? What is the definition of AI? I don’t know.

What are the 10 core components of talent? – summary

People often focus on just 1 component of talent: Crystallized intelligence (e.g. historical skills, knowledge, experience, etc.) and ignore the other 9.  This often leads to major problems, because historical skills, knowledge, and experience are quickly becoming obsolete.

#1 Self Awareness

#2 Character

#3 Relationship skills:

#4 Communications

#5 Crystallized intelligence

#6 Fluid intelligence

#7 Cognitive skills

#8 Ability to quickly learn and unlearn: paradigms, frameworks, methodologies, data, facts, knowledge.

#9 Creativity

#10 Physical capabilities.

What are the 10 Core components of talent? – details

#1 Self Awareness

What are the two types of self-Awareness?^1.

• Internal self-awareness: How clearly we see and understand ourselves. Understanding what our competitive strengths, weaknesses, and capabilities are.
• External self-awareness: understanding how other people view us.

What is the value of self awareness?

• How can you succeed if you don’t know how others perceive you, and which perceptions you need to change? E.g. Decision makers who would hire you or promote you? Customers who would buy from you? Someone deciding whether or not to become your spouse?
• How can you succeed if you don’t understand your capabilities, the implications of your capabilities, and which ones to change? E.g. I’ve met people who have limited skills in certain areas but at the same time hope that companies that are looking for world class skills will hire them. The result is they don’t get hired, sometimes accompanied by massive disappointment.
• Internal self-awareness is associated with happiness, and higher job and relationship satisfaction.¹
• Employees perceive leaders with higher external self-awareness as: having better relationships with them and being more effective leaders.¹

How many people have self-awareness?

• Most people believe they are self-aware.¹
• Only 10-15% of people have self awareness.¹
• 87% of Stanford University MBA students rate their academic performance above the median. 94% of U.S. college professors rate themselves superior to their colleagues. 2
• 96% of leaders believe their people skills are above average. 3

What are the challenges in gaining self-awareness?¹

• People don’t always learn from experience. Experience leads to over-confidence in self-knowledge
• The more power a person has, the more likely they are to over-estimate their skills and abilities.
• People who spend time in introspection are less self-aware, have worse job satisfaction, and well-being

#2 Character

• VME (Values, Morals, and Ethics) Warren Buffett supposedly said “..looking for people to hire, you look for three qualities: integrity, intelligence, and energy. And if you don’t have the first, the other two will kill you.”
• Courage: It takes courage to make the right decision. The right decision is often not: the cheapest, easiest, lowest risk to the company, lowest risk to you, and what everyone else is doing.
• Perseverance, especially against all odds.
• Knowing when to stop persevering. One leader told me “If you’re digging yourself into a hole, stop digging.”

#3 Relationship skills:

• The ability to create and sustain a network of personal relationships.
• Persuasion and negotiation, which is key to managing different points of view and interests.
• Creating and maintaining followers. A leader without committed followers is not a leader.
• Industry disruption and major change require the identification and creation of new relationships and spending less time on obsolete relationships.

#4 Communications

Communications activities include:

• Writing, speaking, singing, drawing, and body language
• Speaking and singing also include tones, pitch, etc.

Communications is two way:

• Broadcasting
• Listening, which includes analysis of input

Communications can have a variety of outcomes, including:

• Understanding other people
• Changing the belief, emotions, and behaviours of others.
• Learning – such as facts, knowledge, ways of thinking.
• Building trust and relationships.
• Persuading people to take certain actions.
• Gaining the emotional and intellectual support of people.

#5 Crystallized intelligence⁴

• Crystallized intelligence is comprised of historical: skills, knowledge (including ways to think, mental paradigms, methodologies), and data.
• The need for crystallized knowledge varies enormously depending on the situation.
• Many years of experience may be very valuable for a doctor doing knee replacements.
• Understanding what customer needs were 5 years ago, and how those were met, may be of little value when: customers have changed; needs have changed; and competition has changed.

#6 Fluid intelligence⁴

• The ability to solve problems without past experience. This is critical for innovation, which is coming up with new and better solutions.
• The future is impossible to predict but actions and decisions are focused on this unpredictable future.
• The future will also be different from the past. i.e. there won’t be historical experience to draw upon.
• Able to provide direction when there is no map. ⁵

#7 Cognitive skills⁶

• Long-term memory
• Working memory: hang onto information while using it
• Logic and reasoning
• Visual processing
• Processing speed
• Attention
  1. Sustained – for long periods of time
  2. Selective – without distraction
  3. Divided – doing two things at once

#8 Ability to quickly learn and unlearn: paradigms, frameworks, methodologies, data, facts, knowledge.

• The founders of the majority of unicorns (startups which achieved a $1 billion valuation) had no previous domain experience. ⁷
• Roche paid $1.9 billion US for Flatiron Health, a cancer electronic records company. The Flatiron founders (Nad Turner and Zach Weinberg) had no background in cancer. They came from advertising.⁸

 #9 Creativity

A Google search of creativity reveals many very different definitions of creativity. Two definitions are:

• “The ability to think about a task or a problem in a new or different way”
• “Creativity involves two processes: thinking, then producing. If you have ideas but don’t act on them, you are imaginative but not creative”

#10 Physical capabilities. These may include:

• Senses, including sight, hearing, touch, smell, taste
• Strength and endurance

How do the core components of talent fit into a typical job description?

The core components of talent fit into the qualification’s sections of a typical job description.

• Job Title:
• Job Summary: High-level overview (2-4 sentences) of the role and its purpose within the company.
• Company Overview: Introduction to the company’s mission, values, and culture.
• Duties and Responsibilities: Primary tasks and essential functions.
• Required Qualifications: Must have skills, education, experience, and certifications. CORE COMPONENTS OF TALENT
• Preferred Qualifications: Nice-to-have skills and experience. CORE COMPONENTS OF TALENT
• Reporting Structure: Who does the role report to.
• Location & Working Conditions: Specifies the job location (e.g., in-office, remote, hybrid) and any relevant physical demands or environmental factors.
• Compensation and Benefits: Often includes a salary range (though not always) and a summary of key benefits like health insurance, retirement plans, and paid time off.

How do the core components of talent fit into a typical job scorecard?

The core components of talent fit into the key competencies section of a typical job scorecard.

• Role Mission: A sentence that defines the ultimate purpose of the role.
• Key Result Areas (KRAs) / Outcomes: A short list (3-5 items) of the measurable results the person is accountable for.
• Key Performance Indicators (KPIs): The specific metrics used to track the KRAs.
• Key Responsibilities / Activities: The primary actions the person will take to achieve the outcomes. This links the “how” (activities) to the “what” (outcomes).
• Key Competencies: The essential behaviors, skills, and traits a person needs to succeed in the role. CORE COMPONENTS OF TALENT.
• Company’s Core Values: Lists the company’s core values to ensure what the employee does is aligned with the core values.

What are the implications of AI?

• An AI worker would have both a job description and a job scorecard.
• If AI is assisting a person in a role, then need clarity on how the AI’s 10 core components of talent are improving the person’s job scorecard.

What are some of the AI challenges?

• What is the definition of an AI worker? What is the definition of an AI agent? What s the definition of AI? Often I hear people explaining something will say “The solution is based on AI”. That is not an explanation. It’s similar to saying “The solution is based on people”
• Since 1993 Visa AI had been deciding whether to decline or accept credit card transactions.
• AI is screening job applications and determining who to interview or not interview.
• AI is making stock buying and selling decisions in high frequency trading.
• Cybersecurity AI is making decisions on what to do with threats without human oversight.

What are your next steps?

• Define the words/concepts you’re using, in a glossary. I’ve seen major confusion when the same words mean different things to different people.
• Review job descriptions and job scorecards. Start with the board of directors and C-Suite.  Measurable results and KPIs are critical.
• Include AI workers and AI assistants in the above.

Footnotes

¹ What self-awareness really is (and how to cultivate it) – Harvard Business Review 2019 January 04

https://hbr.org/2018/01/what-self-awareness-really-is-and-how-to-cultivate-it

We’re all above average

2 https://www.northcoastjournal.com/humboldt/were-all-above-average/Content?oid=4206392&media=AMP+HTML

Aspiring to leadership: Technical knowledge vs people skills

3 https://smartleaders.ca/aspiring-to-leadership-technical-knowledge-vs-people-skills/

⁴ Fluid vs crystallized intelligence

https://www.simplypsychology.org/fluid-crystallized-intelligence.html

⁵ The five new foundational qualities of effective leadership, PWC, Strategy+Business, June 14 2023

https://www.strategy-business.com/article/The-five-new-foundational-qualities-of-effective-leadership

⁶ What are cognitive skills?

https://www.mindmattersjo.com/what-are-cognitive-skills.html

⁷ Ali Tamaseb, Super Founders, New York, New York, Hatchette Book Group, 2021, Page 49

⁸ Ibid., 53

 What further reading should you do?

What is learning? Koor and Associates

https://koorandassociates.org/creating-business-value/why-have-your-minimized-your-talent/

Is your company planning to fail? Koor and Associates

https://koorandassociates.org/avoiding-business-failure/is-your-company-planning-to-fail/

Appendix A What are the core skills that will be even more important in 2030 than 2025.

The following core skills are important in 2025 and will be even more important in 2030.  Who believes this? Over 1,000 global companies with over 14 million employees.  The following ranking reflects the % of companies that believe both core in 2025 and more important in 2020. ¹

• Analytical thinking
• Resilience, flexibility, and agility
• Leadership and social influence
• Creative thinking
• Technological literacy
• Curiosity and lifelong learning
• Talent management
• AI and big data
• Systems thinking

What are core skills required in 2025, but will not increase in importance in 2030?

The following ranking reflects the % of companies that believe both core in 2025 and 2030.¹

• Motivation and self awareness.
• Empathy and active listening.
• Service orientation and customer service.
• Resource management and operations.

How valuable are the core skills which will be more important in 2030?

Let’s use a simple example to show the value of core skills. Which of the two following two companies will be more successful?

Company A board of directors:

• Analytical thinking – jumps to conclusions with little evidence. Make decisions based on gut feelings and personal anecdotes.
• Resilience, flexibility, and agility – cannot deal with sudden unexpected changes in the business environment. Update the strategic plan once a year.
• Leadership and social influence – poor communications with shareholders, C-Suite, employees, etc.
• Creative thinking – relies on outdated mental models and past successes. Rejects new ideas because don’t fit the current way things are done. Focuses on minimizing risks.
• Technological literacy – don’t ask the specific problems technology investments will solve. Defer all technology decisions to one technical expert on the board. Do not use current technology, e.g. AI tools, to carry out their board duties.
• Curiosity and lifelong learning – little curiosity. Board decisions based on 10-year-old understanding of customer needs and solutions.
• Talent management – unable to determine talent requirements for a CEO who will be successful in an uncertain and turbulent future. Unable to assess CEO candidates for future success, resulting in poor CEO performance and company performance.
• AI and big data – not setting metrics for AI initiatives to directly impact value creation. Not understanding the AI talent, and talent compensation, required to drive competitively differentiated customer perceived value propositions.
• Systems thinking – focus on symptoms and not able to identify root causes. Cannot identity that their decisions will have follow-on reaction. Struggle to deal with complex and inter-related problems. The analogy is: if playing chess, don’t consider possible future moves, even the reaction to the first move.

Company B board of directors:

• Analytical thinking – asks for data, metrics, and assumption behind recommendations. Focus on metrics which drive value to customers, employees, and investors.
• Resilience, flexibility, and agility – Recognize that it is impossible to predict the future. Use scenario planning. Review and revise strategies whenever facts and assumptions change.
• Leadership and social influence – excellent communications with shareholders, C-Suite, employees, etc.
• Creative thinking – challenges the status quo and proactively seeks unconventional ideas.
• Technological literacy – questions focus on the customer and business impact of technology investments. Use current technology to carry out their board duties e.g. AI tools.
• Curiosity and lifelong learning – recognize that much of their own historical knowledge and experience is out of date. Regularly bring in experts to update the board. Takes advantage of the advisory board supporting the board. Continuous personal education to have current and relevant knowledge.
• Talent management – the board has long-term process to assess and develop successors for the CEO and C-suite. Company continues to succeed as CEOs and C-Suite members change.
• AI and big data – directors are using AI tools to challenge and validate what company leaders are telling the board.
• Systems thinking – recognizes that the company (directors, C-Suite, employees, customers, investors, etc.) exist in a complex inter-related ecosystem. Understands the interrelationships and how business success is impacted by this ecosystem. The analogy is: if playing chess, considers possible future moves, even the reaction to the first move.

Footnotes

¹ Future of Jobs Report 2025, World Economic Forum Jan 07, Page 41

https://www.weforum.org/publications/the-future-of-jobs-report-2025/

 

What is learning? V3

 What is the purpose of this article?

• This article enables a discussion about what is learning and the best ways to learn.
• The audience for this article includes: board of directors, C-Suite, founders, and investors.
• This article does not provide tax, legal or financial advice.
• You must do your own research and fact-based analysis using current and relevant information.
• AI did not write this article. 100% human written.

You can download a PDF of this article from: What is learning V3

What are the critical learnings in this article?

• Learning is a biological process of changing your brain structure. The key changes to enable learning are new connections between neurons and strengthening the connections.
• The best way for you to learn is to create your own conclusions and recommendations based on your own analysis of data you’ve collected.
• The worst way for you to learn is to read reports and attend presentations.
• Learning and unlearning is hard to do, especially if you’ve been a successful leader.

What is learning?

• Learning is the relatively permanent change in your talent.
• The 10 components of your talent are: Self awareness; character, relationship skills, communications, crystallized intelligence, fluid intelligence, cognitive skills, ability to quickly learn and unlearn, creativity, and physical capabilities.
• All talent is based on the biological structure of your brain i.e. your neurons and the synapses which connect your neurons.
• Learning is a biological process of changing your brain structure. The key changes to enable learning are new connections between neurons and strengthening the connections.

Why do you learn?

You learn for 3 reasons:

• Curiosity
• An external reward e.g. get a promotion or keep your job
• Your own recognition that you your have a gap between your current talent and the talent you need to solve a problem or reach a goal

What is the best way for you to learn?

Active learning is the best way to learn. E.g.

• The best way for you to learn is to create your own conclusions and recommendations based on your own analysis of data you’ve collected.
• Coaching or teaching someone else is the second-best way to learn.
• Other good ways to learn are: simulation & role playing, and case study analysis.

All the above approaches engage multiple parts of your brain and significant change your neural connections.

What are the worst ways for you to learn?

The following passive learning approaches don’t result in any significant learning i.e. sustainable change in behaviour and knowledge.

• Reading reports
• Attending presentations, lectures

All the above have limited changes to limited parts of your brain. As a result, you gain little deep understanding, long term skills, and knowledge retention. BUT, if you take notes while listening to a presentation or reading documents, your learning is improved.

Why is learning hard for you to do, especially if you’ve been a successful leader?

Learning also requires unlearning.  The world is changing faster than ever before.  Crisis and turmoil are never ending.  The future is unpredictable.

What are the psychological barriers to your unlearning?

• Unlearning is the conscious process of recognizing that your past skills, experience, and mental models are of limited or no value now.
• You were an expert – able to successfully do things without deeply thing about it. Unlearning takes you back to making mistakes, which can be very disturbing to you.
• You have become emotionally attached to your mental models.
• Your past expertise and experience are part of your identity. Information which contradicts your past, triggers defensive mechanisms to protect your ego.
• Learning involves mistakes and uncertainty. This is very uncomfortable for leaders who like to project competence and confidence.
• Past successes create the cognitive bias that overestimates your ability in new areas. This results in your believing that you don’t need to learn.

What are the neurological barriers to your unlearning?

• When those skills and knowledge that resulted in your success are challenged, your brain triggers the same defensive and emotional stress response as when you are in physical danger.
• Your brain has developed many short cuts to enable fast decision making. But when the world that created those short cuts has changed, or when your brain is overloaded, you’ll continue to make those same short cut decisions – which are no longer valid.
• When you’re under stress, the part of your brain that detects danger, reduces access to the planning and reasoning parts of your brain. When you are in high anxiety, you are incapable of learning new or complex information.
• When you first learn something, you need your prefrontal cortex to go through intense conscious concentration and effort to create neural connections which connect external input to your behaviours and decision. Repetition over time results in your subconscious and automatic behaviours and decisions.
• Unlearning is a painful process which requires your prefrontal cortex to consciously suppress your automatic behaviours and decisions AND to create new neural connections which will be stronger than your old neural connections. Your old neural connections are not deleted but become weaker over time.

Can everyone learn?

• Many leaders can learn.
• Many leaders are unable to learn. They cannot overcome their psychological and neurological barriers to learning. The lack of self awareness results in total conviction that they do not need to learn.
• In today’s hypercompetitive and turbulent world, the only way for leaders and their companies to succeed is to learn faster and better than competitors.

 What are your next steps?

• Define the words/concepts you’re using, in a glossary. I’ve seen major confusion when the same words mean different things to different people.
• Identify which situations requires learning and unlearning vs those situations where you can rely on your automatic behaviours and decisions, based on your historically successful mental models.
• Identify those few critical business decisions which require you to maximise your learnings.

 What further reading should you do?

What are the core components of talent? Koor and Associates

https://koorandassociates.org/creating-business-value/core-components-of-talent/

Is your company planning to fail? Koor and Associates

https://koorandassociates.org/avoiding-business-failure/is-your-company-planning-to-fail/

Note taking is key to value creation. Koor and Associates

https://koorandassociates.org/creating-business-value/note-taking-is-key-to-value-creation/

AI talent – what is it? V2

 What is the purpose of this article?

This article enables business leaders to begin a discussion of what is AI and the value talent.

The audience for this article includes: the board of directors, C-Suite, and investors.

This article does not provide tax, legal or financial advice.

You must do your own research and fact-based analysis using current and relevant information.

You can download a PDF of this article from: AI Talent – What is it V2

What are the critical learnings in this article?

• Generative AI is software which creates content, such as text, that has never existed before.
• ChatGPT-4 doesn’t “understand” text in the human sense. It’s predicting text based on patterns it learned during training.
• Directions and questions to ChatGPT-4 are transformed into floating-point numbers, then analyzed using a large database of floating-point numbers. The result of the analysis are floating-point numbers which are then turned into text.
• Fundamentally, ChatGPT-4 can be viewed as an advanced form of a word predictor, but it’s a highly sophisticated one. ChatGPT-4 doesn’t “understand” text in the human sense. It’s predicting text based on patterns it learned during training.
• Scientists are sill experimenting with, and trying to predict and explain, the advanced capabilities of Generative AI.

What was the approach used to create this article?

I asked ChatGPT-4 Plus Turbo questions in December 2023 and January, February, May 2024. I summarized the answers in this article.

The scope of this article is ChatGPT-‘s abilities with text questions and text answers. I recognize that in May2024, a variety of AIs are also able to create: voice, song, image, video, spreadsheets, PowerPoint presentations, word documents, etc.

What is AI?

AI is software which simulates human intelligence, with behaviours such as learning and problem solving

How many types of AI are there?

There are two types of AI:

• Narrow or weak: These are designed and trained for a specific task such as a virtual assistant.
• General or strong AI: These have the ability to perform any intellectual task a human can. As of Feb 08 2024, these are still theoretical and don’t exist

How many branches of AI are there?

There are 6 branches:

• Machine learning: makes predictions or decisions based on data.
• Deep learning: a subset of machine learning, based on multi-layer neural networks.
• NLP (Natural Language Processing): Can have a dialogue in a natural human language.
• Robotics: software than performs tasks autonomously.
• Expert systems: Solve complex problems in a way that looks like a human decision maker.
• Computer vision: Can interpret visual images.

Software solutions may incorporate some, or all, of the branches of AI.

When were commercial software tools available for the different branches of AI?

1950s beginning of using computer for tasks that mimic human cognitive functions.  E.g. Logic Theorist.

1980s expert systems designed to mimic the decision-making processes of human experts.

1990’s, 2000’s AI technologies embedded in more generalized software, without being identified as AI.

2010s Machine learning, deep learning and big data.

2020s Large Language Models.

Is Google search an example of AI?

Yes. Some of the AI technologies in Google search include:

• Natural language processing;
• Semantic understanding: understanding concepts, relationships between words ,and context
• Ranking Algorithms: ranking search results based on the authority of a website, quality of content, and how well it matches the search query.
• Machine learning algorithms: machine learning continuously improves search algorithms, based on user interactions and feedback.

What is generative AI?

Generative AI is a type of technology that is designed to create or generate new content such as text, images, music, and code that is often undisguisable from content created by humans. The AI has been trained on large amounts of existing content.

 What is ChatGPT-4?

ChatGPT is software developed by OpenAI. It’s designed to generate human-like text based on the input it receives. ChatGPT can answer questions, write essays, create stories, and perform a variety of language-based tasks

What does GPT stand for?

GPT stands for “Generative Pre-trained Transformer.”  “Generative” indicates its ability to generate text, “Pre-trained” means it has been trained on a large dataset before being fine-tuned for specific tasks, and “Transformer” refers to the type of neural network architecture it uses.

How much data was used to generate the ChatGPT-4 model?

• 45 Terabytes of data was used to create the ChatGPT-3 model.
• Third party estimates are that 100s of terabytes of data were used to create the ChatGPT-4 model.

How big is the ChatGPT-4 model?

• Third party estimates are that the model has from 1.76 trillion parameters to 100 trillion parameters.
• I used the Perplexity AI search engine to find this information. ChatGPT-4 did not provide me with helpful answers.

What is a parameter?

A parameter is a floating-point number.

That’s right.  100s of terabytes of data are processed to create a data base of up to 100 trillion floating-point numbers.

Is ChatGPT-4 A Large Language Model?

Yes

What is a Large Language Model?

A type of AI designed to understand, generate, and manipulate human language. The “large” refers to the large number of parameters they contain, which can range to the hundreds of billions.

What is a Small Language Model?

The basic functionality is similar to a Large Language Model. There are fewer parameters, ranging from tens of thousands to a few hundred million. The models have few capabilities to: understand complex language and context, and the create appropriate content.

What are the steps to create a Large Language Model?

• Research and Planning (defining objectives and designing the architecture)
• Data collection, cleaning and preprocessing (filtering harmful or irrelevant content)
• Model development: choosing a machine learning framework and creating a prototype to validate the concept.
• Training the model: pre-training on the initial data. Adjust the hyperparameters to optimize performance. Manage the computing resources to train the model.
• Evaluation and refinement: metrics-based performance evaluation. Fining tuning with more specific data. Analyze errors to improve the model.
• Implement additional features
• Testing
• Deployment
• Continuous improvement: monitor performance and make improvements. Update with new data.

How many people are required to create a Large Language Model?

The team size could range from 20 people to hundreds.  The skills could include: research scientists and machine learning engineers, data scientists and data engineers, software developers, systems administrators, product managers, ethics and compliance officers, quality assurance and testing specialists, and technical writers and documentation specialists.

What the major steps Chatgp-4 goes through when asked to do something?

• The text is transformed into floating-point numbers.
• Then these numbers are processing by the floating-point numbers in the model.
• The output is floating-point numbers.
• The output is then transformed into text.

Fundamentally, is ChatGPT-4 a word predictor?

• Yes, fundamentally, ChatGPT-4 can be viewed as an advanced form of a word predictor, but it’s a highly sophisticated one.
• ChatGPT-4 doesn’t “understand” text in the human sense. It’s predicting text based on patterns it learned during training

How does ChatGPT-4 do mathematical, financial, and statistical analysis?

ChatGPT-4 has tools capable of performing mathematical, financial, and statistical analyses

 Do scientists understand why Large Language Models are able to do what they can? Do scientists have models which can predict the behaviour and capabilities of Large Language Models?

The basic mechanism (e.g. predicting the next word in a sequence based on training data) are well understood.

As the models have gotten larger, they have capabilities that are difficult to predict or explain.

The following did not come from ChatGPT.  They are a few quotes from the article “Large language models can do jaw-dropping things. But nobody knows exactly why”  The article was published in the MIT Technology Review March 04, 2024.

• “We don’t know what capabilities GPT-5 will have until we can train it and test it”
• “Lots of people have opinions” but no consensus about what exactly is going on
• “The biggest models are now so complex that researchers are studying them as if they were strange natural phenomena, carrying out experiments and trying to explain the results.”
• “Most of the surprises concern the way models can learn to do things that they have not been shown how to do.” “This is one of the most fundamental ideas in machine learning – and its greatest puzzle”
• “Large language models are a whole new mystery”

I still don’t understand, and cannot explain in simple terms, how ChatGPT-4 can write a birthday greeting in the style of William Shakespeare.

What are your next steps?

• You must do your own fact-based research. The bulk of the above article was based on ChatGPT-4 responses.
• Define the words/concepts you’re using, in a glossary. I’ve seen major confusion when the same words mean different things to different people.
• Identify the role. The role could be a team (such as the board of directors) or an individual.
• Define the long-term value of the role in your company’s future scenarios. Outline the metrics for measuring the value of the role.
• Determine the talent components required for the role. You can use the talent components in Appendix 1, or develop your own. If you already have documented talent components, review to ensure they are comprehensive.
• This can be people, technology, or some combination
• Define the criteria for assessing and recommending an option. These criteria include risk management. Determine how to manage risk when the outcomes of software solutions cannot be predicted or modeled.
• Define the options for providing talent. These options could be: people, technology, or some combination.
• Technology can range from very simple software, through different types of data/knowledge retrieval, through different types of analytical tools, through different types of AI. And there can be a combination of software.  Software can include tools and software packages. Generative AI and Large Language Models are not always the answer for every need.
• Prepare an ongoing assessment and development process for the role. In the current, and future, hypercompetitive world, talent capabilities must continuously improve.  In the future, technology may play a greater, or lessor, part in a role.
• Two additional factors to consider: Is a role part of the career development process for people? What will be the impact on career development if the role is automated? Is the value of the role included building and maintaining a relationship with people?  Will those people be able to have relationships with roles that are automated?

 Appendix 1 – The 10 core components of talent¹

• Self Awareness
• Character
• Relationship skills
• Communications
• Crystalized intelligence
• Fluid intelligence
• Cognitive skills
• Ability to quickly learn and unlearn
• Creativity
• Physical capabilities

Footnotes

¹ What are the core components of talent? Koor and Associates

https://koorandassociates.org/creating-business-value/core-components-of-talent/