Mal Fletcher
Tech Predictions 2024 - The Big Shakeup

We face the reality that machines can improve their own programming and the possibility that they might eventually develop consciousness and overtake humanity.

Key takeaways

  1.  The next big thing may be Q star (Q*) artificial intelligence, trained on logic not language.
  2. With brain implants, who owns the data generated by my thoughts? The possibilities for technology creep are endless.
  3. Will AI systems go on producing outcomes long after we think we’ve deactivated them?
  4. We can't delegate responsibility for ethical AI to capitalist markets where the only rule might be, “if a thing can be done, it should be done.”

The Oxford Dictionary Word of the Year in 2023 was rizz. Never heard of it? Don’t worry, you’re not alone. It’s a very GenZ noun describing sexual attraction.

In 2024, rizz might be supplanted by something far less sexy - neurasthenia. Actually, this is not a new word at all. It was coined in the English language in the 1870s. But it might just make a come back in the year ahead.

For the good folk of the late 1800s, neurasthenia described the nerve-racking impact of revolutionary new technologies - like railways and the telegraph. Today we can substitute these tools with Artificial Intelligence (AI), machine learning (ML) and artificial general intelligence (AGI).

A couple of years prior to the Covid outbreak, while addressing civic leaders in Berlin, I was asked what I thought might become the greatest plague of our time. Even today, in the wake of the pandemic, my response would be much the same. The most impacting plague of our age is likely to be a psycho-emotional one. It is the worrying sense that everything in our world is uncertain and fluid, that we’re standing on shifting ice floes and there’s nowhere solid on which to plant our feet. In an word: neurasthenia.

In the 1970s, futurist Alvin Toffler predicted that technological advances would give rise to a “roaring current of change” that which would make people feel insecure and disorientated. He called it “future shock”. We are living in the fulfilment of that prophecy.

A number of factors feed into this overriding sense of uncertainty. One is the shaky position of society’s great institutions. As the Edelman Trust Barometer global survey has illustrated every year for the past decade, almost all of our foundational institutions, including government, the courts, media and business, have suffered a trust deficit, a persistent downward slide in the levels of public trust they inspire.

Climate change is another factor. In particular, the dystopian picture painted by some activists, who apparently feel little or no confidence in humanity’s ability to innovate its way through problems.

Coming up quickly on the inside lane, though, is technology, especially systems powered by AI and ML. Acronyms like these meant nothing to the general public five or ten years ago. Today, we face the reality that machines can improve their own programming and the possibility that they might eventually develop consciousness and overtake humanity. Even technology “evangelists” are worried, including some pioneers of these emergent tools.




Before we take a deep dive into the big techs of 2024, we should note a few things. The first is that when we speak of AI we’re talking about intelligence in a value-neutral way. Machines are amoral. We are the moral agents, who must make ethical choices about how we will use technology.

Second, AI refers, at least at this point in time, to “narrow” intelligence. AI systems are good at carrying out complex single-focus tasks, like winning a game of chess - or Go. They’re not so good at dealing with multiple-focus tasks simultaneously, in the way that the human brain does all the time. 

So, for the moment at least, we are nowhere near achieving an artificial general intelligence (AGI), which will perform any task at least as well as a human. That said, the rate of progress is growing all the time and much of the fear people feel about AI is related to machine learning.

Computer networks are able to analyse, in very short time, entire oceans of data. They can spot anomalies and patterns in the data and from these they can infer rules for behaviour. Thus they can improve their own programming, they “learn”. 

In light of this, people fear that machines will develop under their own steam in ways we can neither understand or control. Some technologists have labelled that turning point the Singularity. We’re not there yet and while we still can we must decide on ethical guidelines for the development of machine intelligence and regulations to back them up. 

In 2024 we have the opportunity to do just that. Generative AI systems, such as ChatGPT, have given people their first hands-on experience of machine intelligence. People are now more aware than ever of the potential of machine intelligence - to do good or harm. 

Meanwhile, competition will heat up for pole position in the design of everything from new generative AI systems to fully autonomous weapons of war. 

So 2024 will be a turning point for technology. 

Here are a few developments that will make the technology headlines in the year ahead.




British Prime Minister Rishi Sunak has said he wants to prioritise both maths education and AI research and development. This year will see the melding together of education and tech development in symbiotic ways. We’ll see breakthroughs in:

Next Level AI: The next big thing may be Q star (Q*) artificial intelligence. Most people have found their introduction to AI through large language models (LLMs). These are so-called because the AI is trained using oceans of language-based data, most of which originates with human beings. Elon Musk says that he bought X (formerly Twitter) because he wants to train his AI using the human-generated data on that platform. 

Q*, on the other hand, refers to AI systems that are trained using mathematics and visual patterns rather than language. They offer exciting possibilities for developing machine systems that understand logic and complex visual puzzles. This will be helpful with everyday activities such as traffic management, but it will also make it easier for machines to have and remember meaningful conversations with humans. This will be a wonderful tool for research and education.

Basing AI on maths models and logic will enable chatbots to serve as maths teaching assistants and tutors. At the same time, better training in maths will empower students to become tomorrow’s AI engineers.

Personalised learning: AI will be used to create personalised learning experiences tailored to students’ strengths, weaknesses, and interests. Outside of school hours, AI-powered tutors will provide students with bespoke instruction, reading lists and feedback. For the 2.5 per cent of children in the UK - and 1.1 million adults - who have learning difficulties, this will be liberating and may end their fear of formal education. 

Immersive learning experiences. Imagine learning a language in a fully immersive environment, rather than piecemeal in a classroom. Or studying historical events by visiting them in virtual space. Virtual reality (VR) and augmented reality (AR), powered by machine learning, will enable you to do both.

Engineers are also working on multi-sensory AI, which will perceive its environment through multiple “senses” that mimic human vision, hearing, touch and smell. This will make AI systems more responsive and immersive simulations more realistic and enjoyable.

Role-Play Training: We’ll see growth in the use of AI to provide interactive role-play situations via chatbots, VR and 3D holographic projection. This will prove very useful in studies with a therapy aspect - for example, training in psychology, medicine and education - or those that involve management and leadership skills. Trainee business students will fine-tune their people-management skills through life-like virtual scenarios. 

Translation and Summation: Imagine lectures that are simultaneously translated into even obscure languages in real-time, without human intervention. Large language models will soon make this available at little or no cost, to students, schools and universities. It will open new doors for distance learning.

Meanwhile, technology will give students access to ancient and obscure writings translated into English and paraphrased into modern writing styles. 

Technology will provide researchers and educators with position papers on key aspects of their subject, calling upon the writings of great thinkers, past and present. AI will collect their thoughts, translate them into modern language and publish them in many forms at once - video, audio, text, graphics and music.




Covid-19 exposed weaknesses in health services the world over. If governments prioritise AI research, they will help services like Britain’s NHS become more future-friendly. In 2024, this will mean:

Personalised medicine: One of the most common complaints about modern medical treatments is that doctors have scant time for patient interaction. People worry that the therapeutic side of medicine is lost to the scientific, box-ticking aspect. 

AI can augment the work of medicos, especially in the analysis of patient data. It can quickly study lifestyle factors, family history and genetics, to build predictive models for personal treatment plans. This will improve the effectiveness and efficiency of healthcare and, in the process, save money.

AI will also support doctors in diagnosing disease. Because of the sheer volume of data it can process, machine intelligence is already as good as or better than human doctors in diagnosing certain forms of cancer, according to recent studies. 

Surgical robotics: In 2024 we’ll hear more about AI-powered surgical robots that perform complex operations. Studies already suggest that, at least in some fields, surgical bots can operate with greater precision than human surgeons. This might improve patient safety and outcomes.

AI and ML will also help provide remote surgeries, featuring a human specialist in one location and a patient in another. This might further democratise the practice of medicine. People living in remote areas will have the same access to high-end treatments as those in better-serviced urban areas.

AI will also allow remote monitoring and diagnosis via advanced Fitbit-style devices.

I’m not suggesting that robo-doctors will replace the human variety. Far from it. At its best, AI will augment, not replace, the work of human physicians. As in many other industries, medicine will rely on humans-in-the-loop systems, not least because only humans can fully empathise with the suffering and healing of other humans.

Blockchain Beyond Crypto: Blockchain is a word little understood outside the often enigmatic world of cryptocurrencies. It refers to a universal online ledger which records every transaction and can be accessed by anyone to keep everyone honest. Its goal is to provide access, security and accountability.

Blockchain technology, though, has other uses. For example, it could be adapted for customer service, allowing people to keep track of goods they’ve ordered. It might provide a means by which citizens could access data stored about them, in the legal system, or on social media platforms, for example.

However, it’s in the world of healthcare that it might find its greatest utility. Blockchain ledgers could provide patients and doctors with easy access to up-to-date medical data and treatment plans. It could help patients keep better track of their use of medicines and the latest updates to prescriptions.

Of course, widespread use of blockchain ledgers would require that hospitals and surgeries constantly update their data security measures. Patients, too, would need to ensure that their access points are secure.

Neural implants: Neuralink is a world leader in developing wireless electrodes for implantation into the human brain. These will be able to send and receive messages from remote computers. With the help of AI, this tech might, in time, alleviate the impact of Alzheimer’s. It might help sight-challenged people to recover some of that faculty. 

It does, however, raise significant moral and ethical questions. For example, who owns the data generated by my thoughts? Do I own it;? Does Neuralink own it? Might some third party, such as a government agency, purchase that data? The possibilities for technology creep are endless.

Drug discovery: In the wake of COVID-19, AI is used to screen large libraries of potential drug compounds to identify those likely to be effective and safe. This will help pharmaceutical companies produce more targeted drugs and do so more quickly as new needs arise.

Of course, regulations must be constantly upgraded to enforce the highest ethical standards in the development and testing of new drugs.

Nanobots: Nanobots represent one of the most misunderstood areas of technology research. A nanobot is a microscopic “machine” - often made of organic, cellular material - which is built from the atomic level up and can be injected into the human bloodstream. If loaded with medical chemicals, nanobots could, in theory, travel through the bloodstream, identifying and taking out harmful cells while leaving the healthy ones intact. 

The latest research involves nanobots that can identify specific types of cancer cells. This technology will not reach its zenith in 2024, but important new steps will be taken in what might become a major part of the future of healthcare. 

Population health management: AI can be used to track the health of entire populations and identify groups that may be most at risk of infection. This information can be used to develop interventions and strategies for entire populations. During the Covid-19 pandemic, data revealed that certain ethnic and locational groups were more susceptible to infection. New developments in Big Data Analysis could provide predictive models that are far more accurate than those used in the pandemic, saving many more lives.

AI predictive models can also help politicians and health authorities gauge the social impact of their policies before they are enacted. 




In 2024, rapidly advancing emergent technologies will boost some industries and damage others. We can expect to see substantial growth in:

Advanced Manufacturing: Sectors covering aerospace, precision engineering and automotive engineering will benefit from tech advances. Particularly because of new developments under Industry 4.0 and the evolution of Smart Factories. Old-school factories are being replaced by smaller production units, each of which is responsible for just one aspect of a large production chain. These units are heavily automated & hooked up via the Cloud. Soon, these units will largely be run by self-repairing, self-regulating machines, with minimal human oversight.

Renewable Energy: AI will help drive the progress of renewable energy projects, particularly in areas like carbon extraction. Wind energy, which generated 715 per cent more electricity in the UK in 2020 than in 2009, will also benefit from advances in machine learning. For example, offshore mobile wind farms rely on predictive models to project likely wind yields at certain times and locations.

Therapeutic Sectors: Empathy is one human skill that machines cannot develop because it requires a shared human experience. Any jobs involving listening and caring skills, therapy or empathy will remain in high demand. They might become much more important, because the greater our engagement with high-tech, the greater will be our need for high-touch. 

Machines can emulate empathy. Social bots in Japanese phone stores and aged care homes are programmed to read emotions via biometrics and respond in kind. But we know it’s not the real thing. There are many areas of life where we need to know that we’re interacting with beings who can truly relate to our experiences.

In law, we don’t always want a robotic magistrate to rule on our case. We will look for the human variety, who can empathise with our foibles and make allowance for mitigating circumstances. (Of course, AI might prove very helpful in advising judges on how to avoid bias in specific judgements. That is if we can help AI overcome its own biases!)

As with medicine, humans skilled in law, education, psychology, religious ministry, physical therapy and so on will be highly valued.

The Arts: According to the Arts Council, England, the arts and culture industry contributes £10.8billion per year to the UK economy. In 2024, we will appreciate the contribution of human artists more than ever, especially given the rise of AI-generated artworks. 

Most AI-generated art, whether in visual or musical forms, is human-curated. It is created using a back-and-forth sequence of programming instructions which provide the parameters for the AI’s activity. 

In 2024, even the best generative AI is still adapting work produced by human beings. Out-of-the-box originality will still prove difficult for artificial intelligence. As AI produces more creative work and that work is networked via the internet, reliance on human material may diminish, but human input will continue to play a role in shaping AI’s creative output, at least for the foreseeable future.

Artists will likely see AI as a collaborative agency. Human artists might well “employ” AI systems as assistants, in the way Renaissance painters did their apprentices.

Some sectors will face a less positive outlook in 2024, because of artificial intelligence. Here are a few to watch:

Manufacturing and office administration: Jobs that involve repetitive tasks are often the first to be automated. Drivers, for example, face the threat of being replaced by autonomous vehicles. 

A 2023 study by Oxford University and Deloitte found that 850,000 public sector jobs in the UK could be lost to automation by 2030. We can expect to see many office administrators lose their jobs, as their core tasks are taken over by software and apps. 

Another study, by Oxford Economics, predicted that robots could replace 20 million manufacturing jobs worldwide by 2030. An increase in automation could boost productivity, by freeing humans from mundane tasks and giving them more time to be creative. This might be useful on the environmental front where innovation will be essential. But automation also raises the potential for income inequality and underemployment.

Underemployment: Over the next few years, a growing number of people will have work, but not enough of it to meet more than their basic needs. It certainly won’t meet their psycho-emotional needs, such as the need to face creative struggle, solve problems and make a meaningful contribution to society. Expect to see the seeds of this emerging in 2024, accompanied by calls from some for a universal basic income.

Professional lay-offs: Professionals working in journalism, medicine and law will be impacted by AI in 2024. The first jobs to be challenged will be those involving proforma tasks, such as filing and collating legal forms or case histories. But higher-end functions will be affected too.

The Do Not Pay app has helped many people fight bureaucracy, negotiate salaries, fight legal fines and much more. It is now being developed to process divorces. Meanwhile, in countries like the Netherlands and Finland, automated speeding fines replace legal figures and administrators who would have previously processed, adjudged and collected those fees.

Robotic surgery is becoming less buggy and journalism is facing huge challenges from output generated by large language models.




There are many other areas in which AI will pose both challenges and opportunities in 2024. For example, there is the vexed question of lethal autonomous weapons systems (LAWS). Several governments are openly researching this area - and we can be sure that others are doing so covertly. This subject is covered in other reports and presentations by 2030Plus.

The bottom line is that AI and ML development raise hugely important ethical questions. The big ethics debates must centre around the following questions:

Human identification: Will we always insist that AI can differentiate humans from machines?

Deliberation: Will AI be able to rein itself in, even if we do not, or cannot?

Latency: Will AI systems go on producing outcomes long after their use-by date - or long after we think we’ve deactivated them? (In war, land mines go on maiming and killing people long after the end of the conflict. Will AI systems similarly produce negative outcomes?)

Discernment: Should we keep ethics as a purely human field of study, rather than turning it over to machines?

Accountability: Will it always be possible for us to trace every AI system back to its developer and user so that we have accountability for actions taken?

We must collectively push for ethics debates sponsored by governments, research bodies and private enterprises working together. 

These must cover a wide range of subjects and bring together experts from diverse specialities - from physics, engineering, biology, medicine, technology and mathematics to ethics, philosophy, psychology and theology. To limit AI in ways that benefit humanity, we must first understand not only the technology but what it means to be human.

We cannot afford to abandon oversight of AI to the egotistic whims of dictators in repressive regimes, who value ideology above humanity. Nor should we leave it in the hands of our own elected leaders, especially when they don’t understand technology. And we can't delegate responsibility for AI to capitalist markets where the only rule might be ultra-pragmatism - “if a thing can be done, it should be done.”

In 2024, we must all overcome our instinct toward neurasthenia. We must work to find safe ways in which to use new technologies, ensuring that they remain our servants, not our masters.


Copyright, Mal Fletcher 2023

Mal Fletcher (@MalFletcher) is the founder and chairman of 2030Plus. He is a respected keynote speaker, social commentator and social futurist, author and broadcaster based in London.

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