Change management modes are used to implement change management efforts in organizations. My MBA students have reviewed several management models, as attached below.
I am a regular fan of beef peperoni pizza, made by a well-known franchisor. As everyone knows, pizza contains one critical ingredient, namely cheese. As pizza is a world favourite food, It is noted that the global worth of the cheese industry is world’s US$150 billion a year. In every pan of pizza, there are about 17 to 26 grams of cheese. Some pizzas have a weighty amount of cheese to delight eaters. According to Rocco’s Random Pizza Facts, each man, woman and child in America eats on average 652 grams of pizza per year. America has a population of more than 340 million.
Presently, most of the cheese used in pizza is derived from milk of cows.
If cows are considered a technology that created milk, they would be 3 per cent effective in converting nutrients. As a former chemical engineer, that is really inefficient technology and nowhere in the world would that technology be accepted. Typically, milk is not complex—it is just water, proteins and other nutrients. We should be able to make this in a laboratory using fermentation process.
Instead of using a 200lb cow to produce dairy proteins, we can use GM yeast (genetically modified yeast) to produce the exact same proteins that are necessary for the production of dairy in laboratories.
One we have the proteins, we mix it with water and nutrients, viola we have milk, which can produce numerous dairy products, such as cheeses.
Let us understand the process of milk from cows. If this process is considered a “technology”, then normal cow milk is produced by impregnating cows. Once the youngling is born. It gets taken way from the mother. The mother will be attached to a milking machine, starting the process of milking over a span that lasts to roughly a year. The milk the cows produce is not effective in converting nutrients they eat (mainly grasses and insects), with a conversion rate of 3 per cent. Then, the cow gets impregnated again, thus, repeating the same process. It is estimated that there are more than 270 million cows that are producing milk in the world. The popularity of pizzas and other dairy products would require more cows and lands to breed them!
Need to have alternatives to produce cheese without cow milk
Genetically modifying yeast can make dairy protein fermentation, easy and simpler method. Bioengineers have been trying to make it the best, most sustainable type of yeast that can create the milk protein, in order to produce the milk products at the faster conversion rate possible. Two main proteins that cows produce that are vital to dairy are casein and whey.
If we can make dairy tastes good (and is the same as traditional dairy), at a comparable price point, no one has to compromise. We would have the dairy we love, at the same availability and convenience as before, just as a much better use of resources, which are finite.
Genetically modifying yeast-the process
The goal of genetically modifying yeast is to alter its DNA so that it has the same protein-producing genes that cows have—so they can produce the same proteins cows do.
We introduce the protein-producing genes to the yeast cells in the form of DNA. Essentially, we are giving the yeast cells an instruction manual on how to make milk proteins by genetically modifying them to include cow DNA. After we introduce the DNA, we want to cell to replicate the new gene sequence many times so that if one is destroyed, we have more copies (cloning the cells).
The genetic engineering process is done through the plasmid of a yeast cell. The plasmid is a circle of genetic material that replicates indefinitely. The role of the plasmid is to transfer genetic information to other parts of the cell. Plasmids exist in addition to the cell’s main DNA (chromosomes). When they are extracted, the yeast cell is still able to function because it has its chromosomes.
In the process of genetic engineering, the plasmid is extracted, and gene edited. A section of the DNA inside the plasmid is cut out, then the DNA sequence that cows use to produce milk proteins is inserted in the cell. The plasmid is then introduced to yeast. It transfers the new genetic information to the chromosomes of the yeast cells. The yeast cells then begin dividing and producing the casein and whey proteins.
In the case of genetically engineered yeast, yeast is the host cell, and the plasmids are edited to include the cow gene sequence that produce proteins. Once we create the transformed yeast cell, we can make the proteins.
Precision fermentation
For thousand of years, humans have used fermentation to produce food and beverages like bread and beer using natural micro-organisms such as yeast.
Recent years saw the rise of biomass fermentation, which use a similar process to create an edible fungal mycelium that is rich in protein and nutrients.
The next evolution is precision fermentation, a high-tech way of making foods and ingredients. Precision fermentation involves engineering a micro-organism like yeast or fungi to produce an animal protein or fat, with the same taste, texture and nutrition as the real kind. Since 1980s, precision fermentation has been used extensively to produce a range of high-value pharmaceuticals and vitamins in fortified foods.
For example, it has been sued to create an enzyme found in rennet that is critical for cheese-making to avoid reliance on animal sources. Similarly, the diabetes treatment insulin is now made within a fermentation tank, so it no longer needs to be sourced from cows or pigs.
Costs have come down in recent years enabling thi technology to be used to produce higher volume, lower value products like food.
Producing cow-free casein
Casein, the unique protein found in dairy milk, can be made without cows by using precision fermentation. It works like a high-tech brewing technique. The aim is to create a factory at the cellular level that continues to multiply and grow significant quantities of casein protein. This is achieved by engineering yeast cells using genetic information from cow’s milk protein, as elaborated earlier.
It is first tested in small flasks in the laboratory where the cells are fed sugar and triggered to start producing the same ingredient. Once the process is working well and casein has the right flavour, taste, and nutrition as what are found in dairy milk, it is time to scale-up. That means increasing production quantities by ten times. Finally, a purification process is undertaken to separate the pure proteins from the GM yeast cells. This leaves just the casein and whey.
Once a product can be developed cost-effectively at this stage, a company may invest in commercial plant where they can then grow to produce 10,000 litres or more. Casein is the essential, functional dairy protein that gives cheese its stretchy, melty properties but had previously only been found in animal milk, such as cows and goats.
Once the cow-free casein is produced, a traditional cheese-making techniques are used, which have been perfected over thousand of years. The cow-free casein is mixed with water, plant-based fats, salt, a small dose of sugar, vitamins and minerals.
Companies involved in cow-free casein
Several companies have been involved in the production of cow-free casein to make cheese for pizzas. They include:
No.
Companies
Countries
website
1
Dairy X Food
Israel
Dairyx.com
2
New Culture
US
Newculture.com
3
Eden Brew
Australia
Edenbrew.com.au
4
All G Foods
Australia
Allgfoods.com
5
Fooditive Group
Netherlands
Fodditivegruop.com
6
Standing Ovation
France
Standing-ovation.co
Besides these companies, other startups are also making cow-free proteins (casein), with some planning market entry via branded consumer products or a b2b strategy.
The market for cow-free dairy protein is huge. It is estimated that the global cheese industry is worth US$150 billion, mainly in the developed countries.
Conclusion
In a few years, we hope the production of cow-free cheese through precision fermentation is significant, thanks to the efforts of the pioneering companies like DairyX and New Culture.
For me, I am interested to pursue the production of animal-free gelatine that is considered “halal” food ingredient for both Muslim and non-Muslims consumers.
Note on milk products
The list of products that you can create from one ingredient of milk is extensive. Add some heat and bacteria, and you have yogurt. Churn it up and you have got butter. Curdle and separate the proteins and you have got cheese. In addition, milk can be drunk and applied to many foods, breakfast cereals and hot beverages.
In milk, casein constitutes about 80 per cent of the protein whilst 20 per cent is made up of whey proteins.
As a chemical engineer, I am closely following the developments and advances in battery technologies, especially for use in EVs. Many research groups are using different materials in the periodic table as an alternative to lithium.
Several electric vehicle battery chemistries are emerging as electric cars .Scientists, battery companies and automakers are trying to develop safe batteries built with accessible materials that enable long driving range and fast charging.
They are working to pack more energy into batteries and cut their expense. This is because batteries is the most expensive component of an EV, adding about US$10,000 more to the cost when compared with a combustion engine powertrain. That expense discourages consumer adoption of EVs and manufacturers are forced to provide incentives to buyers, resulting in lower profit margins of automakers.
Globally, about 60 percent of electric vehicles rely on lithium nickel manganese cobalt oxide, or NMC, batteries, according to the International Energy Agency. Though others are in production, NMC chemistry batteries account for most of the EVs sold in the U.S. Lithium iron phosphate, or LFP, batteries are a growing alternative. They are less expensive and account for about 30 percent of EVs, mostly from China.
The cost and energy density challenges presented by current battery chemistries are pushing companies to seek alternatives that are cheaper. They also need to be safe and ideally would be durable, powerful and suitable for domestic mass production.
“There are a bunch of potentially promising alternatives to lithium ion batteries,” said Jeremy Michalek, director of the vehicle electrification group at Carnegie Mellon University in Pittsburgh. “But all of them have engineering challenges, and potentially some of them have cost challenges.”
Collectively, the industry is researching new chemistries and different ways to physically construct battery cells.
Many believe solid-state battery cells are the holy grail for safe, long-range, fast-charging EV batteries, but until that technology is commercialized, companies are developing alternatives. Here are a few.
New options
Sodium ion: Battery developers are testing sodium chemistries because sodium is less expensive, more abundant and more easily mined than lithium, according to the Department of Energy’s Argonne National Laboratory. The lab patented a cathode material that replaces lithium ions with sodium. The group estimates that a sodium ion battery would cost a third less than a lithium ion battery, and the sodium ion cell also contains manganese and iron, which are widely available. A short driving range is the downside to sodium ion, the lab said. Sodium metal is about three times heavier than lithium, which adds to the battery weight and limits range.
At least two Chinese companies have announced plans for EVs powered by sodium ion batteries, but “the jury is still out in the West,” said Conrad Layson, senior alternative propulsion analyst at AutoForecast Solutions.
Australia, Chile and China continue to dominate lithium production, according to a BP analysis of data from the U.S. Geological Survey and British Geological Survey World Mining Data. Sodium is plentiful in the U.S., said Reeja Jayan, associate professor of mechanical engineering at Carnegie Mellon University.
“It is an evolving battery chemistry so there’s a good chance to establish yourself better in that area,” she said.
Lithium manganese iron phosphate: Manganese, iron and phosphate are generally affordable and available. This chemistry blends the best of nickel cobalt manganese cells with the best of lithium iron phosphate cells, said Nathan Niese, global lead for electric vehicles and energy storage at Boston Consulting Group. The lifespan is shorter than a lithium iron phosphate cell, but energy density is higher, he said.
Lithium sulfur: Lithium sulfur chemistries have a relatively high energy density and can charge quickly, Layson said. Sulfur is extremely abundant and inexpensive, compared with the cobalt and nickel needed for the nickel cobalt manganese aluminum chemistries used in EVs today, according to the Argonne National Laboratory. Lyten, a lithium sulfur battery supplier, said its batteries will launch this year in nonautomotive applications such as drones and satellites. Long term, lithium sulfur cells could cost half as much as the nickel cobalt manganese chemistries used in today’s EVs and with potentially double the energy density, Lyten said.
Solid-state advancements
Automakers and battery makers consider solid-state batteries as a key technology. They are investing in the technology that is expected to enhance range, charging speed and safety.
Semisolid state batteries offer similar benefits and are closer to commercialization.
The semisolid options have small amounts of liquid or gel that quickly diffuse ions to charge and discharge an EV battery. Traditional lithium ion batteries are flooded with liquid electrolytes, which are more fire prone.
Many companies are trying to commercialize semisolid or solid-state technology for the U.S. market.
QuantumScape, a California company backed by Volkswagen and Microsoft co-founder Bill Gates, has developed a ceramic electrolyte technology that eliminates dendrite-forming graphite anode . China controls the bulk of the global supply of battery-quality graphite.
QuantumScape expects to begin high-volume production of cells for advanced testing in 2025, said Asim Hussain, the company’s CMO. QuantumScape and PowerCo. — Volkswagen Group’s battery company — partnered to industrialize QuantumScape’s technology.
Partnering is the fastest way to achieve gigawatt-hour-scale production, the companies said. Depending on the progress of the partnership, QuantumScape will license PowerCo. to mass produce battery cells based on the QuantumScape technology platform.
Factorial, a semisolid battery developer, delivered test samples to Mercedes-Benz in June. 2024. The testing includes validating the module and pack designs against Mercedes-Benz’s performance specifications. Factorial also has joint development agreements with Stellantis, Hyundai Motor Co. and Kia Corp.
Solid Power, a Colorado company backed by and working with Ford, BMW and Hyundai among others, is pursuing the same sulfide electrolyte technology as Toyota.
Chinese companies also are pushing hard on solid-state battery development.
Solid-state technology is advancing quickly, QuantumScape CEO Siva Sivaram told Automotive News. Industrialization is the next step.
“It is not ‘Can I do it?’ It is ‘Can I do it in volume and scale and deliver to customers?’ ” Sivaram said. “There are many steps between here and there.”
Conclusion
The chemistries of batteries are advancing very quickly. Many companies in the US, Europe, Japan and China are racing to be the first to develop new batteries with high energy density that can be produced cheaply with safer operations. Those successes will ensure a greener environment for us, our children, our grandchildren and future generations.
However, many of us continue to drive powerful cars with higher consumption of expensive petrol and diesel. In Malaysia’s case, the efforts of the Malaysian government to eliminate diesel subsidies created negative comments from ta large section of the Malaysian population, citing inflation would become high, which now stands at about 2.0 per cent.
Many years ago, I came across an inventor who had developed a helmet contraption that can treat baldness. I asked him to explain the workings of the helmet, but he refused. He said that he did not want to reveal this. I did not think the helmet contraction worked as I saw only a tiny of small hair follicles growing on his scalp..
He did convince me that the market for his helmet contraption was huge. The fear of going bald is something that weighs on the minds, and scalps, of millions of men around the world.
Recently, a group of scientists from the UK and Pakistan have found a potential cure for male pattern baldness.
Researchers from the University of Sheffield and COMSATS University Pakistan discovered that a sugar which occurs naturally in our bodies can stimulate hair growth in mice.
The sugar, 2-deoxy-D-ribose (2dDR), was just as effective at restoring hair to the balding rodents as commercially available drug minoxidil, also known as Rogaine, the drug owned by Johnson and Johnson.
Professor Sheila MacNeil, of the University of Sheffield, says: ‘This could offer another approach to treating this condition which can affect men’s self-image and confidence.’
The researchers had not originally set out to find a cure for baldness, but were rather investigating whether the sugar 2dDR could help improve wound healing.
When applied to the skin in the form of a gel, the sugar triggers increased growth of blood vessels which they hoped would cause cuts to close faster.
However, they soon noticed that the mice’s hair grew back much faster in the areas around the wound where the gel had been applied.
Intrigued, the research team decided to conduct an experiment to determine whether 2dDR could have an effect on male pattern baldness.
Mice were treated with testosterone to induce ‘testosterone-driven hair loss’ which is similar to male pattern balding in humans.
The researchers found that, after 20 days of treatment, both the sugar gel and minoxidil had promoted 80 to 90 per cent hair regrowth in mice with male pattern baldness.
Combining the two treatments, however, led to no noticeable improvements.
Professor MacNeil says: ‘Our research suggests that the answer to treating hair loss might be as simple as using a naturally occurring deoxy ribose sugar to boost the blood supply to the hair follicles to encourage hair growth.’
Male pattern baldness, or androgenic alopecia, is believed to affect between 40 and 50 per cent of men worldwide.
The condition is caused by a combination of genetic factors and levels of sex hormones which gradually lead to the permanent loss of hair follicles on the head.
Other research has recently suggested that the body’s ‘integrated stress response’ could lead to slowing hair growth and hair loss.
A follicle cell may become stressed, for example, as it ages and becomes less able to properly produce hair, slowing down growth.
And when the mechanism is over-activated, the hair follicle can even die and put a stop to any future growth.
However, as Professor MacNeil points out, ‘at the moment there are only two FDA licensed drugs to treat it.’
Patients can use the topical treatment minoxidil, sold as Rogaine, which can be slow and does not work for everyone suffering from hair loss.
Those who do not see improvements with minoxidil can also take the oral drug Finasteride, sold as Propecia, which works by decreasing the flow of testosterone.
However, this must be taken continuously once started and can be associated with severe side effects such as erectile dysfunction, testicular pain, reduced libido, and depression.
The researchers hope that their breakthrough with 2dDR sugar gels could provide a safer, naturally occurring alternative to these treatments.
he sugar 2dDR occurs naturally in the body as one of the components of the building blocks of our DNA – helping to form the deoxyribose part of deoxyribonucleic acid (DNA).
And, instead of altering the level of sex hormones like Finasteride, the treatment simply works by increasing the amount of blood which can reach the hair follicles.
In tests, the researchers found that this treatment caused the individual hair follicles to sprout long, thick, healthy hairs.
Professor Muhammed Yar, of COMSATS University Pakistan, says: ‘This pro-angiogenic deoxy ribose sugar is naturally occurring, inexpensive and stable.
‘This makes it an attractive candidate to explore further for treatment of hair loss in men.’
I hope this new discovery for treating baldness will benefit millions of men (as well as women), including me. When I met the inventor, I have a full crop of bushy hair,
Reference: Wiliam Hunter. Daily Mail, UK, July 25th, 2024.
Leaders are critical in the performance of organizations at any stage of their life cycles. The slides attached describe some examples of leadership styles that can be adopted by innovators in guiding the growth of their firms.
Since last semester, I have asked my MBA students to write essays on a certain management topic using the ChatGPT. Several essays were excellent while most others were not interesting readings. Many students were able to submit excellent essays, despite their lack of proficiency in English. ChatGPT was obviously helping students to write business reports and analysis despite English being a second language.
I have met many entrepreneurs in 2023 who would apply AI models in various business applications for sales and marketing, and stock investment decisions.
Many articles and analysis are predicting that AI will have more impacts in many areas and would upend specific sectors in developed economies and developing countries in Asia and Africa.
The London Telegraph on December 28th, 2023, in an article written by James Titcomb, noted that employees at OpenAI did not expect much on November 30 2022 when the company unveiled a “low-key research preview” called ChatGPT.
Greg Brockman, OpenAI’s president, told staff that it wouldn’t have much of an impact on day-to-day business, confidently forecasting that it would only get noticed in a few nerdy corners of Twitter.
It quickly became obvious that this was a wild underestimate. Millions of users signed up within days and ChatGPT was dubbed the most important technology in a decade, leading to a worldwide fervor about artificial intelligence.
Employees could be forgiven for failing to predict its popularity, though. ChatGPT, with its ability to conjure up essays and arguments, may have astonished its early users, but to its developers, it was positively medieval.
The underlying AI system it was based on, known as GPT-3.5, was almost a year old. The company had already developed its successor, GPT-4, and was preparing to release it to the public.
OpenAI described it as being 10 times more advanced, saying it could understand not only text but images; and could pass legal examinations.
Now, just over a year later, the company is taking its first steps toward a vastly more powerful system.
ChatGPT founder Sam Altman has warned over AI’s existential risk to humanity. Those who worry that AI is an existential risk to humanity fret that new systems are being developed before we have got our heads around the existing ones.
Either way, the release of GPT-5 is expected to be the AI event of 2024.
Developing computer software is typically a case of tweaking previous versions to eke out small improvements.
Creating new AI systems – known as large language models – is often a case of starting again. An unprecedentedly vast amount of data is thrown at an unprecedentedly powerful system of next generation microchips, resulting in a model several times more powerful than what came before.
GPT-1, the primordial model created in 2018, was trained on 117 million data points known as parameters. GPT-3 required more than one thousand times that, at 175 billion, and GPT-4 was another 10-fold increase, at 1.7 trillion.
The computing requirements have increased too. GPT-4 reportedly required 16,000 high-end Nvidia A100 chips, against 1,024 for the previous generation. Little is known about the next wave of models, but they are certain to be trained on Nvidia’s new H100 chips, a vastly more powerful successor that is the first to be specifically designed for training AI models.
“The history of computer science and AI has been that increased scale results in substantial improvements,” says Oren Etzioni, the former chief executive of the Allen Institute for AI.
“The step up from GPT-3 to GPT-4 was so dramatic, that you would be a fool not to try it again.”
Google, which unveiled its new model Gemini in December, is preparing to release the more powerful Gemini Ultra in the new year. Anthropic, the Amazon-backed AI lab, may also launch a new system.
Scientists are divided, though, on exactly what more powerful will mean. Today’s large language models are approaching the upper limits on certain tasks. Google’s Gemini already outperforms humans on a widely used language comprehension test and on computer programming exams.
That does not make it any less prone to common criticisms of today’s AI models: that they lack creativity, only regurgitating what they have been fed; and that they have a poor understanding of truth, making them prone to “hallucinating” facts.
Experts such as Nathan Benaich, the founder of investment firm Air Street Capital and the co-author of the annual State of AI report, says the next generation of systems will be “multimodal” – capable of understanding text, images, videos and audio. That, he says, will bring them closer to understanding the world.
Demis Hassabis, the head of Google’s Deepmind lab, has said this could come to include sensations such as touch, which could lead to the systems being embedded in robots that can understand the world.
The next wave of models could display capabilities akin to reasoning and planning – qualities that we might associate with human intelligence.
AI that can switch from one task to another would be a step towards autonomous “agents” – systems that can carry out tasks on people’s behalf, such as booking a holiday or reading and answering emails.
The consequences of that could be profound. While today’s AI systems have threatened to take jobs in areas like copywriting and design, they must typically be chaperoned through the writing or illustrating process. Those that can turn their words into action – a customer service bot that can book flights, for example – would be more threatening.
These predictions are largely guesses, however. And even today’s AI models are too complex to completely understand.
This is one of the reasons the next wave of models will face increasing government scrutiny. Nine companies – Amazon, Anthropic, Google, Inflection, Meta, Microsoft, Mistral, OpenAI and Elon Musk’s x.ai – have agreed to have their systems tested by the UK government’s AI Safety Institute before they are released.
Companies have signed up to similar commitments with the White House in the US. The most advanced version of Google’s Gemini model is believed to be going through screening by officials before its upcoming release.
Equally, the next wave of AI systems could prove to be a bust. Sceptics believe that most of the low-hanging fruits have already picked, and that improvements from this point will be marginal no matter how much computer power is deployed.
But if the capabilities of next year’s models remain unknown for now, it seems certain that existing AI technologies will become more widely used.
In 2023, AI may have captured the popular imagination, but it might not be until 2024 that its impact really starts to be felt.
Ai models are likely to provide solutions to problems that typically small- and medium-sized companies face every day: high staff turnover, lack of skills and available manpower, sales staff, accounting, and compliance.
In 2024, my company, Bison Consulting, will be working with AI partners to offer services using AI models.
We could learn from my wife’s “steno moment”. In 1980’s many young girls in small town learned short-hand writing to become stenographer. When the Wang word-processor was introduced, the demand for stenographers disappeared, and many short-hand writing schools closed. Today, there is no position called stenographer in firms.
The rise of advanced AI tools such as ChatGPT and Stable Diffusion, which generates images based on text prompts, has generated fears that jobs would be substituted by the technology.
One of first studies into the impact of AI on the jobs market in the UK, carried out by the Department for Education (DfE), has concluded that consultants, accountants and psychologists are most exposed to the rise of AI.
Sports players, roofers and construction workers were among those least likely to be affected by the technology.
People with higher levels of education are more likely to be impacted than those with lower level qualifications.
The research refers to “exposure” to AI systems, meaning jobs may be aided or replaced by AI. However, careers that are aided by AI may also generate fewer jobs if it means technology can accomplish key tasks.
Official statistics divide professions in the UK into 365 categories, such as solicitors, librarians and nurses, although some jobs are categorised more widely, such as financial managers.
The DfE’s provided an “AI occupational exposure (AIOE) ” score to each job based on AI’s ability to replicate the skills required.
The scores range from around -2 to 1.5, with a higher score indicating a profession is more likely to be affected.
The DfE said it was generally believed that between 10pc and 30pc of existing jobs will be affected by AI, although new jobs will also be created to take advantage of the technology.
A study from US researchers earlier this year found that AI tools like ChatGPT were already taking freelance work away from copywriters and graphic designers.
The DfE said: “The report illustrates how the education system and employers will need to adapt to ensure the workforce has the skills necessary to benefit from this emerging technology.”
Men of the cloth have persevered for millennia, surviving the separation of church and state, the industrial revolution and multiple world wars.
Yet vicars and priests are now under threat from a very modern scourge: chatbots.
Jobs in the clergy are among the most exposed to the rise of artificial intelligence (AI), according to a government report.
Clergy members were ranked as the 13th most exposed to “large language model” systems out of the 365 categories of occupation studied.
They were deemed slightly less likely to be affected than local government administrators, but slightly more vulnerable than university lecturers.
The figures were based on what key skills are used in each profession, such as written comprehension and inductive reasoning, and how easily they could be replicated by AI.
The study may have missed unique aspects of individual professions and the research does not speculate how precisely the technology could influence each job.
Concerns about AI’s impact have increased in the last year as a result of advances in systems such as ChatGPT, which is already being widely used in the workplace.
Generative AI systems, which are capable of rapidly processing and generating text and images, are already disrupting the job market by leading to fewer opportunities for freelance copywriters and illustrators.
The DfE said its report showed that the education system and employers alike would have to adapt to provide more training as existing jobs are disrupted.
The report said it did not distinguish between jobs that were likely to be aided by AI and those that were likely to be replaced, and that it was based on a “number of uncertain assumptions”.
Economists had expected educated, white-collar workers to be the least exposed to the rise of AI before the arrival of ChatGPT, which has reversed assumptions about what jobs are vulnerable.
AIOE (AI Occupational Exposure and AI applications)
Felten et al (2021) have developed the AIOE measure based on Ai applications of AI that are likely to have implications for the workforce that cover the most likely andmost common uses of AI. Below is the list of AI applications.
Ai application
Definition
Abstract strategy game
The ability to play abstract games involving sometimes complex strategy and reasoning ability, such as chess, go or checkers, at a high level
Real-time video games
The ability to play a variety of real-time video games of increasing complexity at a high level.
Image recognition
The determination of what objects are present in a still image.
Visual question answering
The recognition of events, relationships , and context from a still image
Image generation
The creation of complex images.
Reading comprehension
The ability to answer simple reasoning questions based on an understanding of text.
Language modelling
The ability to model, predict , or mimic human language.
Translation
The translation of words or text from one language into another.
Speech recognition
The recognition of spoken language into text
Instrumental track recognition
The recognition of instrumental musical tracks
Readers who are interested on the AIOE measure should read the following:
Occupational, industry and geographic exposure to artificial intelligence: A novel dataset and its potential use. Strategic Management Journal, 42 (12).
E. Felten, M. Raj, and R. Seamans (2023). How will Language Modeller like ChatGPT affect occupations and industries?
DfE. The impact of AI on UK jobs and training. November 2023.
