Dear Reader,

I hope you are doing well and having a relaxing early start to the summer (at least where I am here in UK). If you were expecting a newsletter from me last week and missed it, I apologize. Since I started writing these newsletters, that was the first time I had not been able to meet the expectation of sending out a weekly newsletter. It has been an awfully busy last week for me.

This week, I am reflecting on these:

1. How will computational modelling be changed by AI
2. Behind the scenes at CM Videos: Tax returns and the like
3. Quote of the week: Skills and mindset

Technical Reflections

How will computational modelling be changed by AI

There has been a lot of anxiety with regards to the impact of Artificial Intelligence (AI) on different job sectors. Beyond just ChatGPT, there is an overwhelming, increasing body of evidence of AI-enabled Plugins that are next level in impacting the way people work today.

It is on that premise that I started exploring the impact of AI on computational modelling, and I believe as an enthusiast of computational modelling, you will certainly be interested in exploring this with me. I think the best place to start is this excellent article written by Loz Blain in the New Atlas magazine titled: "Which jobs will AI hit hardest, and which will stay safe the longest?"

Which jobs are most at risk by AI?

The figure shown below is taken from the above work and gives a graphical representation of the industries (a) least t at risk (dark blue), (b) then those most at risk (grey) and finally (c) those where AI will complement existing skillset (light blue).

The headline conclusions are these:

1. Office and administrative support work will be impacted most by AI
2. Also, the legal sector will also be impact most by AI
3. However, non-automated tasks like building, cleaning and maintenance will not be affected
4. Computational modelling will benefit from a complement between existing skills and AI.

What does this mean for computational modellers?

In view of the above, and similar findings as above, here are my advice for you as a computational modeller:

1. Keep upskilling: The emergence of AI is not the signal to death of skills acquisition. AI is fantastic and will help you do a whole lot but you must understand the basics. The skills you have will be complemented by what AI can do for you. However, the skills you do not have will not be amplified at all by AI. Imagine multiplying zeros skills by a million capability of AI, it will still result in zero. On the contrary, if you have 0.1 unit skill, and multiply it by say a 1000 units of AI-enabled ability, you will be at least up to a 100 units. So, keep upskilling.
2. Embrace AI unreservedly: I will advice that you join the crusade for AI-enabled computational modelling as there is great potentials here. I know we have two partisan groups of AI users (see my article here about this). We have Techno-utopians who happily embrace AI and think it will revolutionize everything; yet we also have Techno-pessimists who oppose AI greatly and castrophize about its destructive tendencies. If you are a computational modeler, you need to choose the techno-utopic approach and begin to explore what AI can do for you. This will stand you in good stead.
3. Enhanced productivity: The availability of AI language models and their corresponding plug-ins means that for a first time, in many years, comptuational modellers can enhanced their productivity by multiple margins. I have seen this at work already in my academic research around AI uses in higher education and computational modelling. Code writing that tends to take me weeks to achieve can be done in a very short time, by leveraging the power of AI.
4. Be schooled in prompt engineering: Prompt engineering has become a buzz word for AI. It refers to the ability to craft (engineer) the right prompt for extracting the sort of outcome you desire from AI models. As a computational modeller, you must be schools in how to craft the perfect prompts for your problem. There are tons of resources online that explore this issue but we are still in the infancy of it. I can visualize a university course where prompt engineering will become offered to help produce graduates who know how to talk to AI and become valuable resources in their organizations. You therefore must begin to explore how to write excellent prompts to get the best from AI tools.
5. Recognize AI-literacy as an employability skill: You have to realize that companies are replacing a lot of job with AI-tools. Therefore, traditional jobs are increasingly becoming the domain of AI tools. There are obvious cost cutting reasons as well as enhanced productivity gains that are driving the decisions of these company boards. As a computational modeller, you must realize that AI-literacy as an employability skills. Just like digital literacy is one, the development of specific skills, understanding and application of AI tools to solve tasks (which I call here AI-literacy) must also be seen as part of now an ever burgeoning basket of employability skills that you and future computational modellers must demonstrate to prospective employers. You must therefore recognize this and work on it.

That is what I think of how AI will impact computational modeller. The person who prepares for this future is the one who will benefit the most from it.

Behind the Scenes at CM Videos

Tax Returns for CM Videos Ltd

I am Director of the CM Videos Ltd - which is the educational consultancy business behind the CM Videos YouTube channel. Part of that role requires that a tax return is made on behalf of the company to the government. It is that time of the year where we make tax returns to the UK's His Majesty's Revenue and Customs (HMRC) service. Since the company is registered as a private limited company here in the UK, the company has to make what is called Corporation Tax to the government. The Corporate tax is tax paid by business to the government's coffers. Oct 2023 will be the second anniversary of the company and the tax for the last (business) tax year is due this October. This is the very first tax accounts that I have to submit to the government.

Using this company, I am able to make tax returns for software products sales by the business, endorsements, brand deals as well as Youtube income that is generated from Ads placed on my videos. It also means that I have to also note carefully all the expenses I make on this business. A lot of expenses have been made in the last one and half year which means the outgoings of the business are quite a lot.

This week, I have been working on filing the tax return. I am trying to do the tax myself even though I know people can appoint accountants and agents to prepare the statement on their behalf. As the business is still at its infancy, I will like to make the tax returns myself and when we grow big enough to require extra hands, then I will decide then. This therefore means I am having to learn a lot about what is required to set up the account, prepare an expenses and income statement that will go with the filed tax account as well as adequately make the tax return. It has been a fun journey and I should be done with it this weekend.

Quote of the Week

Skills and Mindset

I read this #1 New York Times Bestseller titled Put your mindset to work, which is co-authored by James Reed and Paul G. Stoltz. Some of you who are aware of the highly popular recruitment agency REED, this is the company that Mr James Reed started. So, he knows a thing or two when it comes to what makes people employable and successful in life. I am taking my quote for the week from the book and here it is:

I am drawn to this quote because a lot of times my students obsess about getting the right skillset to be employable. They do a lot of certification courses, undertake post-graduate students and they never seem to have enough skills. Yet, I see others who might not have so much skills but end up being employed in the most lucrative of roles. The more I study these students, I realize the first set have a lot of self-doubt thinking that only their skills will make them employable. The later category have a lot of self-believe, who though not so skilled, take whatever skills they have and go for the job irrespective of whatever barrier they might come in contact. It is this latent self-belief that Mr Reed addressed as mindset.

To be able to excell i n the computational modelling space, you do not need to be proficient in MATLAB, Python, ABAQUS, ANSYS, CREO, SolidWorks, Google SketchUP, C++ and other computational modelling tools. You might have these and still find yourself failing to land the job. That is not to say having them is not a great addition but there is something more.

Mindset is an internal drive that you phrase within yourself seeing that you are qualified for that job. It is a motivation that takes you before a potential employer and with that confidence coming through, you state what you can and where you cannot do something, you offer a confident defence on how you can become good at that. Current educational systems do not always teach or inculcate mindset within you. You have to find ways to do so.

I thought I should share this as I find it a real differentiation between skilled students and lesser skilled one, where the later have an overwhelming belief in themselves. If you have the former, maybe begin to work on the later so you can be sufficiently equipped for what next life throws at you.

Thank you for reading this far. I appreciate your continued readership of this newsletter. If you have enjoyed it, do share with your friends. I will catch up with you again next week and in the mean time, cheers!