TL;DR:

• Prepare for AI age by improving learning skills.
• Develop effective, efficient learning through style, content, curation, and critical thinking.
• Choose right content, medium, and evaluate creators for successful learning.
• Practice curation and critical thinking to filter valuable information.
• Master learning skills to adapt and thrive in AI age.

First off, a heartfelt thank you

Yes, thank you to all you readers who made my last article on this website “Does Your Business Really Need an AI Strategist?” a top trending article on this website, and thank you AIinASIA for publishing these articles.

So what are focusing on today?

Off the back of this, a lot of you reached out with different questions and concerns… and so this new article has been written in direct response. Grab yourself a coffee, get comfortable and welcome to the next article in this series of The View from Koo!

How to prepare yourself for the age of AI:

First, some context: a lot of my friends and participants of my courses are young parents. One of the top things on their minds were, what should they have their children to learn. The parents’ concern – and really, the top concern on everyone’s mind – is a worry that AI will eventually take over our jobs and cause seismic shifts in our industries… leading to a need to find another job.

Remember: you’re not going to be able to escape the impact of AI. So how best to prepare for it?

Current Trends Are Intriguing, But It’s Not All Doom and Gloom

The current trend is while Artificial Intelligence does not take over jobs right now, it will take over certain tasks. As Artificial Intelligence take over more and more tasks, jobs which is a basket of tasks, can be replaced eventually.

It is either that or Artificial Intelligence will change the nature of jobs since it is a tool. You can see it as a dirt digger at a construction yard, from using the shovel to an excavator.

Artificial Intelligence will either change the nature of your job by increasing your productivity, moving you to higher value-added tasks, or make your job obsolete (think long-haul drivers and supply chain workers).

A Single Key Skill to Have to Unlock Your Future!

If I were to go to ‘First Principles’ I would say the single key skill to pick up and become more resistant to the waves of changes brought about by Artificial Intelligence is embrace the “Learning Skill” – meaning: how to learn effectively and efficiently.

Innovate and pivot

As waves of changes keep coming, we can either be proactive and pick up new skills that we believe will be in high demanded later, or be forced to learn new skills when changes hits hard and potentially embrace retrenchment or our businesses may become bankrupt.

The next 3-5 years will bring uncertaintly and we will all be in a constant state of flux and we will need to continue to learn new skills such as operating new software, technology or latest best-practices.

This translates into the need to keep learning. The spoils will go to those that are proactive, and able to learn effectively (able to apply) and efficiently (understand in a short amount of time).

So Let’s Talk About Learning

As a fellow lifelong learner, trainer and mentor, I see that there are THREE dimensions you need to look at to improve your learning skill. They are: learning style, content, curation and critical thinking.

Learning Style

Learning gets better with practice and having lots of self-awareness. The more you learn, the more practice you get. The more you learn, the better you understand your learning style. Getting to that learning style is important as it makes your learning more productive. But getting to that learning style requires time and experimentation.

You need to experiment while learning at the same time.

For instance, spending time listening to audiobooks versus reading physical books, learning from an instructor versus self-directed learning, or writing notes versus recording and listening to notes.

Content is everything: Medium and People

For content there are two sub-dimensions to look at: Medium and People.

There are many mediums that we can use to learn from. There are videos, websites, physical books, e-books, podcasts, classrooms, workshops, short-courses, degree programs etc. You can see them as delivery channels of content. Choose the deliver channels that suit your style of learning.

Content is generated by people, think professors and lecturers in your degree or diploma program. To learn better, we need to start questioning the background of the folks who are generating the content. Are they the right people to learn from? As I always say:

If you want to be rich, learn from the rich. If you want to be a professional soccer player, you learn from a professional soccer player.

We need to start questioning the background of the content generators. Do not fall into the influencers in “expert” clothing trap.

Critical Thinking & Curation To Cut Through the Noise

We are in the information age where information is in abundance. I am sure you have heard of disinformation and misinformation and you do not want to fall victim to it as it hurts your credibility as an individual and in your career.

What can we do with the information avalanche? How can we quickly differentiate the truth from the “fake news” stains?

In a self-directed or from classroom learning, we want to pick up the skills, knowledge and information that is going to be useful. This is where we need to do curation and critical thinking:

Curation will help to quickly reduce the delivery channels we need to pay attention to. Critical thinking will help us to quickly differentiate what we should pick up and learn from.

You can start practicing curation by always looking at and figuring out the content producers are they really experts or the schools that are putting out the courses are they credible in the fields and what is the background of the instructors, and critical thinking comes in to quickly ascertain whether the content shared is it going to be useful for your circumstances.

Critical Thinking and Curation as you practice more of it will make your learning better!

So Where Does This All Lead Us?

We need to start to learn how to learn. Learning skills will help us to stay ahead of the curve, ensuring that we can not only survive but to thrive in the Age of AI.

However, learning how to learn is not taught in any former education institution and thus it is up to us to pick it up.

To be able to learn effectively and efficiently, we will need to quickly be aware of our learning style, focus on getting good content, the medium and producer, that suit our styles and last but not least, practice, practice and more practice, especially on our Critical Thinking and Curation skills.

Comment and Share:

Do you have any tips on how to learn better? Share your thoughts in the comments below as we hone our learning skills together, and don’t forget to subscribe for updates on AI and AGI developments.

You may also like:

• 15 Advanced Brainstorming Techniques Powered by ChatGPT
• Mastering AI in Asia: Training ChatGPT to Mimic Your Unique Voice
• Or find out more about Koo’s company, Data Science Rex.

TL;DR:

• Not all businesses require an AI Strategist; an established data management process and optimised reporting are prerequisites.
• AI is just one tool in the data toolkit, and not all business problems require AI solutions.
• A Data Strategist with expertise in data management, analytics, and machine learning might be a better fit for most companies.

Thoughts from Data Scientist expert, Koo Ping Shung

Hi, I’m Koo. I’ve been working with Data and Artificial Intelligence for over 20 years. I’ve done all sorts of things like collecting data, managing it, and making sure it’s used properly. I also help to find useful information from data and put it into machine learning models. Every now and then, I notice what’s happening and what’s difficult in this field and I write about it.

Lately, I’ve seen a lot of people using the title “AI Strategist”. I also get asked about this a lot at my company Data Science Rex (DSR). So I thought it was time to share my thoughts.

So… grab a coffee and settle down as we unpack whether your business really needs an ‘AI Strategist’. Here’s a humble view from a Data Scientist:

The Prerequisites of AI Adoption

Firstly, there are certain conditions that need to be met in your business before you start thinking of hiring an AI strategist.

1. Data

We all know that AI works better when there are good quality data, followed by availability of relevant data. So, you need to assess whether your business has an established data management process first. What is an established data management process then? It should have the following:

Infrastructure:

Are there established data storage and retrieval infrastructure? It needs to be something like a data warehouse, a SINGLE place where all the datasets go to be stored and managed.

Data Management Processes:

Are there data management process that accompanies the infrastructure? In order to ensure your data is of good quality, it needs to be managed well. This is not forgetting that there should be processes in place to ensure high security and privacy level. These are processes that deals with Identity & Access Management or IAM in short.

Data Quality Measurement:

Are you measuring data quality? Data quality needs to be measured to build up confidence in using data. Having established data quality metrics helps in showcasing to your stakeholders that the reports or derivative products from data such as insights, visualisations and analysis can be trusted.

2. Reporting

Have your organization optimised your reporting process using data? Why is business reporting important before coming to AI?

We need to actively understand the nuances of data by examining how and when the data is collected and determining what each column in the dataset represents.

Only through a good understanding of these nuances, that are honed through multiple reporting, can we have a good understanding on what are the limitations from internal data.

Establishing AI through your business requires change management extensively. This means that throughout your business, there is a need for everyone to understand how data and AI works, followed by everyone feels that they have benefitted from using data.

An optimised reporting process throughout the company is a good signpost to say that your business and its employees have benefitted from data for their own tasks.

3. But… Do You Really Need AI for your digital transformation?

Once these conditions have been met, there’s a good chance that if there are AI use cases in your organisation, you may be successful. The reasons are it has tackled two of the biggest roadblock to adopting Artificial Intelligence in business, Data and Change Management.

AI is just part of the data toolkit. You can see AI as, besides the ubiquitous tools that you find in the toolkit like hammer, screwdrivers, etc, that smart shiny drill that can auto-change the drill bit based on your needs.

From this analogy, you will realise that not all your business challenges are about “drilling” i.e. AI solves certain type of problems, not all problems. What does this translate? Not all the business problems you have needs AI, and followed by do you have enough AI use cases to justify hiring a full-time AI strategist?

Do not forget that AI use cases like any IT projects has costs to it, short-term being the proof-of-concept, design & planning, data management, training of the AI models, and long-term being the maintenance, constant monitoring and validation of AI models, cloud computing subscription, ensuring the essential skills stays within the organization.

Switching Perspectives

Now put yourself in the shoes of an AI strategist, let us forget about his/her background, experience and suitability for the role for the moment.

The AI Strategist main role is to identify areas in the business where AI can be used, proposed the necessary changes that needs to be made, and how AI should be integrated into the business process, keeping in mind the alignment to strategic goals of the business.

Have you ever heard of the saying, “To a hammer, everything is a nail.” To an AI strategist…everything must use AI? Wait a minute! You probably realise right now, a few paragraphs before, we did mention that not all use cases need AI! AI is just one of the tools in the data toolkit! If a simple average is needed to solve a business challenge, why go through all the hassle and the costs (short- & long-term)?

4. So What Do I Need?

Data will be the new normal, and taking advantage of data will be what good business leaders will constantly be thinking about. There are multiple tools, with variation in value derived from data, that business can take advantage of, and Artificial Intelligence is part of it.

What you really need is a Data Strategist, that can help your business see end-to-end from data collection all the way to change management when the derivatives of data, such as decision models or insights, are being used in business processes.

I could write a whole article on how you should select a Data Strategist for your organisation (let me know in the comments below if you’d like to read this), but to give some quick pointers, the person needs to have background in the following:

• Data Management & Data Quality
• Data Analytics & Data Analysis
• Machine Learning, Model Deployment & Model Monitoring
• Generic Business Processes & Change Management

I can tell you very quickly such talents are not easy to find. But a word of caution, do not jump onto one because of the titles. Titles are easy to award, but of most importance is their experience and background! Be comfortable with it.

And please remember:

“AI is not a one-size-fits-all solution, and other data tools might be more suitable for specific problems. It works better when there are good quality data, followed by the availability of relevant data.”

I wish your company all the best in building up data capabilities and taking advantage of data analytics and artificial intelligence (if any). –– Koo

Comment and Share:

Have you considered the benefits of a Data Strategist for your business instead of an AI Strategist? Share your thoughts below and don’t forget to subscribe for updates on AI and AGI developments. You can also connect with Koo Ping Shung on LinkedIn by tapping here.

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TL;DR:

• Human consciousness is a vast and deep phenomenon with roots in cellular intelligence.
• AI and AGI are challenging human intelligence, necessitating its evolution.
• Understanding our connection to life can guide ethical choices and shape the future of AI and AGI in Asia.

The Vastness and Depth of Consciousness

As we delve into the intricacies of artificial intelligence (AI) and artificial general intelligence (AGI), it’s crucial to examine the foundations of human consciousness. Recent neuroscience recognises two primary forms of consciousness: creature consciousness and mental state consciousness.

The former is attributed to all organisms with a nervous system, while the latter is associated with more complex nervous systems, allowing beings to experience the world and their relationship to it (LeDoux, 2023, 219).

However, a third category, existential consciousness, has emerged, rooted in cellular intelligence as an expression of living, self-organising order (Reber, Baluska, and Miller, 2024). This perspective highlights the vastness and depth of consciousness in life, extending beyond the presence of a nervous system.

The Evolution of Consciousness and Life

Life on Earth, estimated to be 4 billion years old, began as single-celled organisms. These ancient prokaryotic organisms invented the bioelectrical aspects of cellular life, laying the groundwork for existential, creature, and mental state consciousness (Derr et al., 2020).

Consciousness, therefore, is a vast phenomenon with deep roots and is still evolving. It is essential to understand that we have not yet reached the end point in the development of possible expressions of consciousness.

The Necessity of Expanding Consciousness

Science has long overlooked the importance of human experience and consciousness. This neglect has created a blind spot, despite lived experience being an inescapable part of our search for scientific truth (Frank, Gleiser, and Thompson, 2024).

An alternative perspective is emerging, intertwining life and consciousness in a coordinated cognitive ecology (Reber et al., 2024). This view offers a valuable lens to examine the deep planetary crises created by humanity and emphasises the need for human intelligence to evolve before AI colonises us.

AI, AGI, and the Future of Human Intelligence in Asia

As AI and AGI advance, particularly in Asia, human intelligence faces new challenges. The natural intelligence of humans differs fundamentally from the artificial intelligence of machines. AI and AGI systems can mimic emotions and consciousness, but they are not conscious. To navigate this new landscape, we must deepen our understanding of consciousness and its roots in life.

In Asia, AI and AGI are being integrated into various sectors, from healthcare and education to transportation and finance. For instance, China’s “Social Brain” project aims to create a network of AI systems working together to analyse and manage data in real-time, optimising city management and services. In Japan, researchers are developing robots with AGI capabilities to assist an ageing population.

These advancements underscore the urgency of understanding the relationship between human consciousness and artificial intelligence.

Ethical Implications and the Role of Consciousness

A deeper understanding of our consciousness and its connection to life can help guide ethical choices in AI and AGI development. Recognising that consciousness is not exclusive to humans and that our actions impact all life forms can foster a more responsible approach to technology.

For example, researchers in South Korea have proposed a “Well-being Impact Assessment” for AI systems, evaluating their effect on human well-being and the environment. This approach acknowledges the interconnectedness of life and technology, aligning with the understanding of consciousness as a deeply rooted and vast phenomenon.

Becoming Fully Human in the Age of AI

Abraham Maslow’s question, “What might be the normal psychological or inner life of persons who are fully human?” remains relevant today (Maslow, 1971, XVII). As we navigate the age of AI and AGI, becoming fully aware of our connection to life is crucial for making ethical choices and shaping the future of these technologies.

The Path Forward

Embracing our role in the living world and recognising the vastness and depth of consciousness can help us evolve human intelligence to meet the challenges posed by AI and AGI. By doing so, we can create a future where technology serves and enhances life, rather than colonising it.

Conclusion: Ethical AI

In conclusion, consciousness is a vast and deep phenomenon with roots in cellular intelligence. As AI and AGI challenge human intelligence, it’s crucial to evolve our understanding of consciousness and our role in the living world.

By recognising our connection to life, we can make ethical choices and guide the future of AI and AGI in Asia and beyond.

Comment and Share on the Future of Human Intelligence:

What are your thoughts on the future of human intelligence in the age of AI and AGI? How can we foster a deeper understanding of our connection to life and make ethical choices in AI development?

Share your thoughts below and subscribe for updates on AI and AGI developments in Asia and beyond.

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• AI: Clever Mimic or True Conscious Companion?
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• Or read the science paper The Cellular Basis of Consciousness by tapping here.