A team of Researchers at Tokyo University have found a way to bind engineered living skin tissue to robots with the hope of benefitting the cosmetics industry and helping to train plastic surgeons.

New Method Of Adhesion 

The team (led by Professor Shoji Takeuchi) has reported that whereas previous methods to attach skin tissue to solid surfaces involved mini anchors or hooks, which limited the kinds of surfaces that could receive skin coatings, the new successful method mimics human skin-ligament structures. The new method uses specially made V-shaped perforations in solid materials, thereby enabling the team to bind skin to complex structures. The natural flexibility of the skin with this effective method of adhesion means that the skin can move along with the mechanical components of robots without tearing or peeling away.

Created A Smiling Face 

Professor Takeuchi highlighted how, in their latest research, the team was able to “replicate human appearance to some extent by creating a face with the same surface material and structure as humans”. The photos of the prototype robot’s skin-covered face show it with a smile (achieved through actuation and via anchors).

New Challenges Identified 

Professor Takeuchi said that although the team has undertaken previous research on a finger-shaped robot covered in engineered skin tissue, this new research identified new challenges for future efforts. For example, the team discovered the need for skin surface wrinkles and a thicker epidermis to achieve a more humanlike appearance, suggesting that creating a thicker and more realistic skin could actually be achieved by incorporating sweat glands, sebaceous glands, pores, blood vessels, fat and nerves.

Looking to a future where robots could be covered in their own living skin layer, Professor Takeuchi acknowledged the importance of movement. He highlighted the challenge of creating humanlike expressions “by integrating sophisticated actuators, or muscles, inside the robot” and expressed how “incredibly motivating” is the thought of being able to create “robots that can heal themselves, sense their environment more accurately and perform tasks”. 

Professor Takeuchi also highlighted the scale and scope of the challenge of creating living skin for robots that’s self-healing, saying that “Self-healing is a big deal – some chemical-based materials can be made to heal themselves, but they require triggers such as heat, pressure or other signals, and they also do not proliferate like cells.” 

He added that “Biological skin repairs minor lacerations as ours does, and nerves and other skin organs can be added for use in sensing and so on.”

Goal 

Although they created a smiling skin face in the research, Takeuchi and his lab are keen to emphasise that they have a serious goal in mind for this application in terms of helping in several areas of medical research. For example, Takeuchi suggests that something like a “face-on-a-chip” could be useful in “research into skin aging, cosmetics, surgical procedures, plastic surgery and more”. Also, Takeuchi said that if sensors could be embedded, robots may be able to gain a better environmental awareness and improve their interactive capabilities.

What Does This Mean For Your Business? 

The apparent breakthrough achieved by Professor Shoji Takeuchi and his team at Tokyo University could signify a profound transformation in various industries, particularly cosmetics and medical training. For businesses in these sectors, the integration of living skin tissue onto robotic platforms presents exciting opportunities.

In the cosmetics industry, for example, this innovation could revolutionise product testing and development. Traditionally, cosmetic products undergo testing on synthetic materials or live animals, both of which have limitations and ethical concerns. However, the use of robots with human-like skin could offer a more accurate and ethical alternative. Companies could test how their products interact with human skin, including how they are absorbed, how they affect skin texture, and their long-term impacts. This method may not only ensure a higher fidelity of results but also align with increasing consumer demand for cruelty-free products.

For businesses involved in medical training and plastic surgery, the ability to simulate human skin on robotic models could be a real game-changer. These advanced robots could provide surgeons and medical students with realistic practice scenarios that better prepare them for real-life procedures. The potential to replicate various skin conditions, responses to surgical interventions, and healing processes on these models could enhance the educational experience and lead to better patient outcomes. Also, the development of self-healing skin technologies could extend the lifespan and utility of these training models, reducing costs and improving training efficacy.

This innovation could also open new avenues in fields such as robotics and human-computer interaction. Robots equipped with human-like skin and the ability to heal and sense their environment more accurately could lead to advancements in service robotics, elderly care, and rehabilitation. Businesses in these areas could see improvements in the functionality and acceptance of their robotic products, as the ability to mimic human touch and appearance enhances the user experience and trust.

The research also hints at future possibilities where robots could be more seamlessly integrated into daily life, performing tasks that require a human touch. For instance, in hospitality or customer service industries, robots with human-like skin could provide more personalised and engaging interactions, setting new standards for customer experience.

Overall, the development of robots with living skin tissue is not just a scientific curiosity but appears to be a significant leap forward with practical implications. Businesses that adapt and integrate this technology early may expect to lead in their respective fields, offering innovative solutions that were previously unimaginable. Whether through enhancing product testing, improving medical training, or advancing interactive robotics, this breakthrough could provide a unique competitive edge and open up a world of new possibilities.

NASA has given Elon Musk’s SpaceX the contract to ‘deorbit’ (and destroy) the International Space Station at the end of its operation as NASA transitions to commercially owned space destinations closer to home.

SpaceX To Develop The Deorbit Vehicle 

US space agency NASA has chosen SpaceX to develop and deliver the U.S. Deorbit Vehicle that NASA says will “ensure a safe and responsible transition in low Earth orbit at the end of station operations”, i.e. it will tow the space station into low earth orbit before it burns up on re-entry. NASA reports that while SpaceX will develop the deorbit spacecraft, NASA will take ownership after development and operate it throughout its mission. NASA also says that along with the space station, SpaceX’s Deorbit Vehicle “is expected to destructively breakup as part of the re-entry process.” 

When? 

The International Space Station has been in operation since 1998 and NASA says the United States, Japan, Canada, and the participating countries of ESA have committed to operating the station through 2030.

How Much? 

The contract for SpaceX to make the Deorbit Vehicle is thought be worth $843 million.

Whose Responsibility? 

Although SpaceX is to make the Deorbit Vehicle, NASA says the safe deorbit of the International Space Station is the responsibility of all five space agencies – CSA (Canadian Space Agency), ESA (European Space Agency), JAXA (Japan Aerospace Exploration Agency), NASA (National Aeronautics and Space Administration), and Russian State Space Corporation Roscosmos.

Where Will It Land? 

It is expected that any parts of the space station and Deorbit Vehicle that don’t fully break up on re-entry will land in the ocean with NASA saying the actions of the Deorbit Vehicle will “ensure avoidance of risk to populated areas.” 

What If It Hits Your House? 

Although NASA’s plans sound good, try telling that to a Florida family who are currently suing NASA after a 1.6lb (725g), 4ins by 1.6ins part from the International Space Station crashed through their roof and floor. Thankfully, none of the family, who are seeking $80,000 (£63,000) for the stress and impact on their lives, were physically injured. According to NASA, the metal part that hit their home was the result of ground controllers using a robotic arm on the space station to release an almost 3-ton cargo pallet containing “aging batteries” back in March 2021.

Mica Nguyen Worthy, the lawyer for the Oteros family, has been quoted as saying: “Here, the U.S. government, through NASA, has an opportunity to set the standard or ‘set a precedent’ as to what responsible, safe, and sustainable space operations ought to look like. If NASA were to take the position that the Oteros’ claims should be paid in full, it would send a strong signal to both other governments and private industries that such victims should be compensated regardless of fault”. 

Space Debris 

Space debris has become a significant problem due to the increasing number of satellites and space missions, leading to a crowded orbital environment. For example, it’s estimated that there are approximately 36,500 pieces of space debris larger than 10 centimetres, about 1 million pieces between 1 and 10 centimetres, and around 130 million pieces smaller than 1 centimetre currently orbiting Earth.

This debris poses risks to active satellites, spacecraft, and indeed, the International Space Station, potentially causing collisions and generating more debris in a dangerous feedback loop known as the ‘Kessler Syndrome’. With this danger in mind, the ‘Space Liability Convention’ of 1972 was created to establish the liability of countries for damage caused by their space objects.

What Does This Mean For Your Business? 

The decision by NASA to entrust SpaceX with the task of deorbiting the International Space Station (ISS) heralds a new era in commercial space operations, signalling some perhaps significant implications for businesses. As the ISS’s operations transition to commercially owned space destinations, companies in the aerospace sector are poised to gain unprecedented opportunities. SpaceX’s $843 million contract not only highlights the increasing role of private entities in space but also the potential for lucrative government contracts and partnerships in an evolving space economy.

For businesses, this shift could mean an expanding market for innovation in space technologies. Companies involved in developing deorbiting vehicles, space debris mitigation, and sustainable space operations may expect increased demand for their expertise. The collaborative approach required by the five space agencies overseeing the ISS deorbiting operation also suggests a growing need for international cooperation and compliance with space liability conventions, making regulatory and legal expertise in space law more valuable than ever.

Also, the challenges highlighted by incidents such as the Oteros family’s lawsuit against NASA underline the importance of risk management strategies. The outcome of this lawsuit could, for example, set a significant legal precedent for how liabilities from space debris impacts are handled, potentially influencing policies and compensation frameworks globally. Businesses need to be prepared for potential liabilities associated with space operations, including debris impact on Earth, and adapt their operations to mitigate such risks effectively.

This scenario presents an opportunity for businesses to develop advanced tracking, monitoring, and risk mitigation solutions to ensure the safety and sustainability of space activities. The case also demonstrates the need for companies to engage in proactive legal and insurance planning to manage potential claims and safeguard their operations.

In essence, the move to commercialise space destinations and manage space debris responsibly potentially opens many of avenues for businesses to innovate and expand. Staying ahead in this competitive landscape will require agility, a commitment to sustainability, and an understanding of the complex regulatory environment governing space operations. As space becomes a more integral part of our economic infrastructure, businesses that can perhaps seize new opportunities position themselves as significant players in the growing space industry.

Finally, on the subject of space, it’s also worth noting here that NASA’s plans to return to the Moon, through the Artemis program, may also bring commercial opportunities. For example, the lunar missions will require new technologies, habitats, and supply chains, presenting another vast market for companies involved in space exploration and infrastructure. A move to greater lunar exploration will undoubtedly bring a need for innovative solutions and partnerships to support sustainable operations, e.g. on the Moon and beyond.

It’s been reported that following the recent announcement that ChatGPT is to be integrated into Apple’s devices and its new “Apple Intelligence” technology is to be across its suite of apps, Apple is to take up an observer role on OpenAI’s board.

Bloomberg reported that with effect from later this year, Apple ‘Fellow’ and head of Apple’s App Store, Phil Schiller, will be attending OpenAI board meetings as an observer (without voting rights).

OpenAI announced in March that it would be appointing new directors to its board, including company OpenAI CEO Sam Altman, Sue Desmond-Hellmann, a former CEO of the Bill and Melinda Gates Foundation, Nicole Seligman, formerly a president of Sony Entertainment, and Fidji Simo, CEO of Instacart. Adding an Apple member to OpenAI’s board will help Apple to keep up with the other main players in the AI race.

A grieving family from Berkshire have reported how online fraudsters used a photo of their recently deceased son on social media to make mourners click on bogus link for a streamed funeral service with the goal of exploiting their grief to get data and cash.

Alex Chadwick’s photograph was used by the fraudsters and although the funeral service was not filmed (despite the fraudsters using a bogus streaming-link), the family have expressed their shock at the criminals’ tactics and have called for legislation to stop it happening to others.

Alex Chadwick’s father Gary has been reported (BBC) as saying that he believed the family had been targeted because his son was young and had a lot of followers on social media.

A new fast-charging battery technology from Nyobolt that can charge an EV battery from 10 to 80 per cent in just under five minutes has just successfully completed its first demo road test.

Live Demo 

Founded in 2019, Cambridge-based EV battery company Nyobolt has just conducted its first live road test demo of the new battery in Bedford, in front of an invited audience of industry professionals. The new battery, which was fitted to a sports car and tested over two days, achieved a range of 120 miles after four minutes. The company says this was achievable because the first four minutes are at a constant current of 500A.

Still A Success Despite Challenges On The Day 

In lab conditions, the fast-charging battery can charge from 0 per cent to 100 per cent in six minutes but on the day, factors like the hot weather, issues with the car’s cooling system, plus having to use an on-site charger (not made by Nyobolt) meant that it only charged from 10 per cent to 80 per cent in four minutes and 37 seconds. However, that is still a very impressive result considering that a Tesla supercharger takes 15-20 minutes to charge a car battery to 80 per cent. Using a 350kW DC charger, Nyobolt says its batteries can charge at twice the speed of the fastest-charging vehicles on the road without the degradation typically associated with lithium-ion batteries.

Fast Charge And Retention  

Nyobolt also points out that independent testing of its technology by a leading global OEM has confirmed that its longer-lasting (and more sustainable batteries) can achieve over 4,000 fast charge cycles, or 600,000 miles, maintaining over 80 per cent battery capacity retention. This is considerably higher than the warranties of much larger EV batteries on the road today and highlights longer-lasting performance benefit of Nyobolt’s battery technology.

Benefits 

The company says its ultra-fast charging battery eliminates slow and inconvenient recharge stops, i.e. it saves time and combats ‘range anxiety’.

In Talks With Other OEMs 

Nyobolt doesn’t intend to make its own EVs but says it is now in talks with eight OEMs about using its technology in high performance EVs.

Lighter EVs 

Nyobolt also says that the fact that the 35kWh battery pack, as tested in the EV prototype, is compact could also benefit car makers and motorists, enabling energy-efficient electric vehicles that are cheaper to buy and run, and use fewer resources to manufacture.

Nyobolt’s co-founder and CEO, Dr Sai Shivareddy says: “Our Nyobolt EV demonstrates the efficiency gains facilitated by our fast-charging, longer-life battery technology, enabling capacity to be right-sized while still delivering the required performance,” and adds “Nyobolt is removing the obstacle of slow and inconvenient charging, making electrification appealing and accessible to those who don’t have the time for lengthy charging times or space for a home charger.” 

What Does This Mean For Your Organisation? 

Nyobolt’s groundbreaking fast-charging battery technology could be transformative for various stakeholders within the EV ecosystem. For Nyobolt itself, this development not only validates their technological innovations but may well also position them at the forefront of the EV battery market. The successful demonstration in Bedford, despite the challenges faced, highlights their capability to deliver a product that can significantly reduce charging times while maintaining high performance and longevity. This achievement is likely to attract further interest from OEMs and investors (8 are interested already), accelerating Nyobolt’s growth and market penetration.

For other EV manufacturers, the introduction of Nyobolt’s technology presents both an opportunity and a challenge. The ability to charge an EV battery to 80 per cent in under five minutes sets a new benchmark in the industry and is likely to compel other manufacturers to either adopt this technology or innovate rapidly to remain competitive. This could lead to a surge in partnerships and collaborations as manufacturers try to integrate these advanced batteries into their next-generation vehicles. Also, the focus on sustainability and longer battery life aligns with the broader industry goals of reducing environmental impact and improving the overall efficiency of EVs.

The EV market as a whole stands to benefit significantly from this technological leap. The reduction in charging times addresses one of the primary concerns of potential EV buyers – range anxiety. Faster charging infrastructure will likely catalyse broader adoption of EVs, as it makes the transition from traditional petrol and diesel vehicles more seamless. The compact nature of Nyobolt’s battery packs means vehicles can be lighter and more energy-efficient, potentially lowering the cost of EVs and making them more accessible to a wider audience. This could lead to a more rapid shift towards electric mobility, reducing the carbon footprint of the transportation sector.

For EV buyers, Nyobolt’s technology promises a more convenient and user-friendly experience, i.e. the ability to recharge quickly and efficiently means less time spent at charging stations and more time on the road. This may be particularly appealing to those with busy lifestyles or limited access to home charging setups. Also, the extended battery life and capacity retention may translate to lower long-term costs and enhanced vehicle reliability. As a result, consumers can expect a more cost-effective and sustainable ownership experience, which could drive higher satisfaction and loyalty within the EV market.

Nyobolt’s fast-charging battery technology, therefore, could herald a new era in the EV industry (which needs a boost about now), offering substantial benefits across the board. From improving Nyobolt’s market position and challenging other manufacturers to elevate their offerings, to making EVs more appealing and accessible to consumers, this innovation could reshape the landscape of electric mobility in the UK and beyond. Organisations within the EV sector will, no doubt, be closely monitoring these developments and considering how to integrate or respond to this technology to stay ahead in a rapidly evolving market.

If you ever find yourself locked-out of LinkedIn, this video is for you …

The Action Centre in Windows 10/11 provides quick access to common settings and notifications. You can customise the quick actions to include the settings you use most frequently. Here’s how:

To open Action Centre:

– Click on the Action Centre icon in the taskbar (or press Win + A).

To customise Quick Actions:

– Click on Expand to see all quick actions.

– Right-click on any quick action and select Edit quick actions.

– Drag and drop icons to rearrange them or click on Add to include new actions.

To save changes:

– Click ‘Done’ to save your customised quick actions.

Two new studies show that Google’s Gemini AI models may not live up to the hype in terms of answering questions about large datasets correctly.

Google Gemini 

Google Gemini is an advanced AI language model developed by Google to enhance various applications with sophisticated natural language understanding and generation capabilities. It features multimodal capabilities, enabling it to process and integrate information from text, images, and possibly audio for more comprehensive and context-aware responses. The model also boasts a deep contextual understanding, allowing it to generate relevant and accurate answers in complex conversations or tasks.

Google has highlighted Gemini’s scalability and adaptability as being its strong points, and how its highly scalable architecture can help with handling large-scale data efficiently and fine-tuning for specific tasks or industries.

Also, Gemini is thought to deliver superior performance in speed and accuracy due to advancements in machine learning techniques and infrastructure.

Studies 

However, the results of two studies appear to go against Google’s narrative that Gemini is particularly good at analysing large amounts of data.

For example, the Cornell University “One Thousand and One Pairs: A ‘novel’ challenge for long-context language models” study, co-authored by Marzena Karpinska, a postdoc at UMass Amherst, tested how well long-context Large Language Models (LLMs) can retrieve, synthesise, and reason over information across book-length inputs.

The study involved using a dataset called ‘NoCha’, which consisted of 1,001 pairs of true and false claims about 67 recently published English fiction books. The claims required global reasoning over the entire book to verify, posing a significant challenge for the models.

Unfortunately, the research revealed that no open-weight model performed above random chance, and even the best-performing model, GPT-4o, achieved only 55.8 per cent accuracy. Also, the study found that the models struggled with global reasoning tasks, particularly with speculative fiction that involves extensive world-building.

The models were found to frequently fail to answer questions correctly about large datasets, with accuracy rates between 40-50 per cent in document-based tests.

The research results suggest that while models can technically process long contexts, they often fail to truly understand the content. Also, the results may highlight the limitations of current long-context language models such as Google Gemini (Gemini 1.5 Pro and 1.5 Flash).

The Second Study 

The second study, co-authored by researchers at UC Santa Barbara, focused on the Gemini models’ performance in video analysis and their ability to ‘reason’ over the videos when being asked questions about them. However, the results also proved to be poor, highlighting difficulties with transcribing and recognising objects in images, thereby perhaps indicating significant limitations in the models’ data analysis capabilities.

Discrepancies Between Claims And Performance? 

Both studies appear to highlight possible discrepancies between Google’s claims and the actual performance of the Gemini models, thereby raising questions about their efficacy and shedding light on the broader challenges faced by generative AI technology.

Posted On X 

Marzena Karpinska, also noted (on X/Twitter) other interesting points about LLMs from the research, including:

– Even when models output correct labels, their explanations are often inaccurate.

– On average, all LLMs perform much better on pairs requiring sentence-level retrieval than global reasoning (59.8 per cent vs 41.6 per cent), but still their accuracy on these pairs is much lower than on the “needle-in-a-haystack” task.

– Models perform substantially worse on books with extensive world-building (fantasy and sci-fi) than contemporary and historical novels (romance or mystery).

What Does Google Say? 

Google has not directly commented on the specific studies that critique the performance of its Gemini models. However, Google has highlighted the advancements and capabilities of the Gemini models in their official communications. For example, Sundar Pichai, CEO of Google and Alphabet, has emphasised that Gemini models are designed to be highly capable and general, featuring state-of-the-art performance across multiple benchmarks. Google asserts that Gemini’s long context understanding, and multimodal capabilities significantly enhance its ability to process and reason about vast amounts of information, including text, images, audio, and video.

Google has tried to highlight its focus on the continuous improvement and rigorous testing of Gemini models, showcasing their performance on a wide variety of tasks, from natural image understanding to complex reasoning. The company has also been actively working on increasing the models’ efficiency and context window capacity, allowing them to process up to 1 million tokens (the basic units of text that the model processes). Google hopes these improvements will enable more sophisticated and context-aware AI applications.

What Does This Mean For Your Business? 

The findings from these studies may have significant implications for businesses relying on AI for data analysis and decision-making. The apparent underperformance of Google’s Gemini models in handling large datasets suggests that businesses might not be able to fully leverage these AI tools for complex data analysis tasks just yet. This could impact sectors like finance, healthcare, and any industry requiring detailed and accurate data interpretation, where businesses may need to reassess their dependence on such models for critical operations.

For Google, these studies may highlight a gap between their promotional claims and the actual capabilities of their AI models. This could prompt Google to accelerate its research and development efforts to address these shortcomings and enhance the practical utility of their models. It also places pressure on Google to maintain transparency about the limitations of their technologies while continuing to push the boundaries of AI performance.

Other AI companies might view these findings as both a caution and an opportunity. On one hand, the discrepancies in performance underline the inherent challenges in developing robust AI models. On the other hand, they provide a competitive edge for companies that can deliver more reliable and accurate AI solutions. This competitive landscape could drive innovation and lead to the emergence of more capable AI models that better meet the complex needs of businesses.

In summary then, while the current limitations of AI models like Google Gemini pose challenges, they also highlight areas ripe for innovation and improvement. Businesses should stay informed about these developments and be prepared to adapt their strategies to harness the full potential of evolving AI technologies.

In this insight, we look at the kinds of industries and jobs that research has identified as being most exposed to the disruptive threat of generative AI, but we also look at how AI has created some new job roles.

Research 

Research from Felten, Manav Raj, and Seamans –“How will Language Modelers like ChatGPT Affect Occupations and Industries?”), from OpenAI and also the University of Pennsylvania offered some reasonably in-depth analysis of how advances in AI language modeling, such as ChatGPT, impact various occupations and industries. As part of the key findings, the research paper identified some of the jobs most exposed to ChatGPT. These findings were:

Telemarketers 

The research indicated a high exposure Level. This is because the nature of telemarketing involves repetitive tasks that could be easily automated by language models. ChatGPT can, for example, handle customer inquiries, provide information, and even persuade potential customers, thereby reducing the need for human telemarketers.

Post-secondary Teachers
(e.g. English Language and Literature, Foreign Language and Literature, History)

According to the research, there is a significant exposure level for these jobs, with the reason being they often require the creation of educational content, as well as grading, plus answering student queries, which are all tasks that ChatGPT can perform efficiently. However, the interactive and mentoring aspects of teaching are much less likely to be fully replaced by AI.

Legal Services 

Famously, ChatGPT (specifically GPT-4), passed the legal bar exam back in March 2023 and exposure to ChatGPT in legal jobs is thought to be considerable. For example, many tasks within legal services, such as document review, contract analysis, and basic legal advice, can be automated using language models. ChatGPT’s ability to process and understand large volumes of text makes it suitable for these tasks.

Securities, Commodities, and Investments 

Financial analysis, report generation, and market trend analysis are all areas where ChatGPT can assist significantly. Specifically, its data processing capabilities can enhance efficiency and reduce the reliance on human analysts for routine tasks.

In fact, the researchers were able to compile a list of the top 20 professions most exposed to ChatGPT, which are:

1. Telemarketers
2. English language (and literature) teachers
3. Foreign language (and literature) teachers
4. History teachers
5. Law teachers
6. Philosophy and religion teachers
7. Sociology teachers
8. Political science teachers
9. Criminal justice and law enforcement teachers
10. Sociologists
11. Social work teachers
12. Psychology teachers
13. Communications teachers
14. Political scientists
15. Cultural studies teachers
16. Arbitrators, mediators, and conciliators
17. Judges, magistrate judges and magistrates
18. Geography teachers
19. Library science teachers
20. Clinical, counseling and school psychologists

Accountants Exposed 

The OpenAI / University of Pennsylvania research (working paper) also found that a significant portion of the US workforce, including accountants, mathematicians, interpreters, and writers, are highly exposed to the capabilities of generative AI technologies like ChatGPT. For instance, the research revealed that at least half of the tasks performed by accountants could be completed much faster using AI, thereby demonstrating the substantial impact of these technologies on various professions.

Not Creative & Management Jobs 

Conversely however, this paper noted that professions requiring human judgment, creativity, and complex decision-making are much less likely to be replaced by AI. These include jobs in fields like:

– Creative arts, including artists, writers, and designers, where the emphasis is on originality and human creativity.

– Management – roles that require strategic decision-making and interpersonal skills.

– Healthcare. Professions that involve direct patient care and complex medical decision-making.

The findings of the OpenAI research suggest that while AI like ChatGPT can significantly impact certain job sectors by automating routine tasks, roles requiring nuanced human skills and judgment appear to remain less vulnerable to automation.

Also, researchers at Northwestern University’s Kellogg School of Management (in the US) examined the historical impact of disruptive technologies on jobs and projected the effects of ChatGPT. Not surprisingly, their findings indicated that jobs involving data analysis and information retrieval are most at risk from ChatGPT.

What Can Workers Do? 

To protect themselves from the threat posed by AI technologies like ChatGPT, workers can focus on developing skills that are less likely to be automated. These include critical thinking, creativity, and complex decision-making abilities. Professions that require nuanced human judgment, such as those in creative arts, management, and healthcare, are less vulnerable to AI automation. It’s possible, therefore, that by enhancing skills in these areas, workers may remain more relevant in an AI-augmented job market.

Also, reskilling and upskilling are possible strategies for workers to stay competitive. Learning new technologies and understanding how to leverage AI tools can turn potential threats into opportunities. Workers could take advantage of AI to increase their productivity and efficiency rather than being replaced by it, suggesting that training programs focusing on AI literacy, data analysis, and digital transformation could also prove to become essential for workers to adapt to the changing landscape.

Integrating AI into their workflow in a way that complements their unique human capabilities may also be a way that workers can mitigate the threat posed to their jobs by AI such as ChatGPT. This could involve understanding how to use AI to augment tasks that require speed and accuracy while focusing on aspects of their jobs that necessitate empathy, interpersonal skills, and complex problem-solving. Embracing a collaborative approach with AI could therefore help workers enhance their roles and provide added value to their employers, thus securing their positions in the evolving job market.

What About AI Creating Jobs? 

It’s worth remembering that as well as posing a risk to certain jobs/roles, ChatGPT, and other generative AI could also create new jobs and opportunities. For example:

AI specialists and engineers. The rise of generative AI has led to an increased demand for AI and machine learning specialists. These professionals are responsible for developing, maintaining, and improving AI systems. According to the World Economic Forum’s Future of Jobs Report, there is a projected 40 per cent increase in the number of AI and machine learning specialists by 2027, highlighting the growing need for expertise in this field.

Prompt Engineers. As AI models like ChatGPT become more prevalent, the role of prompt engineers has emerged. These specialists create and refine the prompts used to train AI systems, ensuring they generate accurate and relevant outputs. This role requires a deep understanding of both the technology and the specific application domains, making it a unique and valuable (as well as a high salary) position in the AI ecosystem.

AI Trainers and data annotators. Generative AI models require vast amounts of data to learn and improve. AI trainers and data annotators play a crucial role in preparing and curating this data. For example, they label datasets, review AI outputs, and provide feedback to enhance the models’ accuracy and performance. This job is critical for maintaining the quality of AI-generated content and ensuring that the models operate within ethical and practical boundaries.

Digital transformation specialists. Organisations are now increasingly integrating AI into their workflows, which is feeding the demand for professionals who can manage and lead these transformations. Digital transformation specialists can help companies adopt and leverage AI technologies effectively, optimising processes and driving innovation. The Future of Jobs Report (World Economic Forum) indicates a significant rise in demand for digital transformation specialists, underlining their importance in the modern workplace.

AI ethics consultants. With the growing influence of AI, ethical considerations are important. AI ethics consultants work to ensure that AI applications comply with legal standards and ethical guidelines. They help organisations navigate the complexities of AI implementation, addressing issues like bias, transparency, and accountability. This emerging role is proving to be important for building public trust and promoting responsible AI use.

What Does This Mean For Your Business? 

The findings from the research on AI technologies like ChatGPT appear to show a real shift in the landscape of various industries. For UK businesses, this translates into a need for proactive adaptation to harness the benefits of AI while mitigating its disruptive potential. Integrating AI into business operations could significantly enhance efficiency, particularly in roles that involve routine cognitive tasks and data processing. For example, automating customer service, financial analysis, and legal documentation could free up valuable human resources to focus on more strategic, creative, and interpersonal tasks. Embracing AI can therefore lead to a more streamlined and productive business environment, reducing operational costs and improving service delivery.

Also, the evolution of AI presents an opportunity for businesses to invest in the reskilling and upskilling of their workforce. Note that there is an argument that genAI like ChatGPT can also have a deskilling effect. By providing training programs focused on AI literacy, data analysis, and digital transformation, businesses can equip their employees with the necessary skills to thrive in an AI-augmented job market. Encouraging a culture of continuous learning and adaptability will not only help in retaining talent but also foster innovation and resilience within the organisation. Workers who are adept at leveraging AI tools can hopefully transform potential threats into opportunities using AI to augment their roles and increase their productivity and value to the company.

Businesses also need to consider the ethical implications of AI deployment. Establishing roles such as AI ethics consultants could ensure that the integration of AI is conducted responsibly, addressing issues like bias, transparency, and accountability. This may not only build public trust but also help safeguard the company against potential legal and ethical pitfalls.

Researchers, led by scientists at UCL and University Medical Center Goettingen, Germany, have developed an AI-enhanced blood test that can predict Parkinson’s in at-risk patients up to seven years before the onset of symptoms.

What Is Parkinson’s? 

Parkinson’s disease is a condition caused by the progressive breakdown of certain nerve cells in the brain, resulting in a deficiency of the neurotransmitter dopamine. This results in symptoms including slowness of movement, increased muscle tension and tremors, and non-motor symptoms like olfactory (sense of smell) loss, plus sleep disorders and even depression.

In the UK, approximately 1 in 350 adults is diagnosed with Parkinson’s disease, which translates to around 153,000 people currently living with the condition. Parkinson’s is the second most common neurodegenerative disease and is becoming increasingly common in the population. For example, estimates suggest that the number of people diagnosed will rise by nearly a fifth by 2025, reaching about 168,000 (Parkinson’s UK).

The Challenge

Up until now, the diagnosis has mostly been based on motor symptoms, which only occur when more than 70 percent of the dopamine-containing nerve cells have already been degraded. Also, there are currently no clues (biomarkers), which can indicate the specific disease process simply, directly, and at an early stage.

The New Research 

The new cooperation project research, however, which involved researchers from the University Medical Center Göttingen (UMG), the Paracelsus-Elena-Klinik Kassel and University College London (UC), appears to have found a simple AI-enhanced way to diagnose the disease early.

How? 

In the first stage, the researchers analysed blood samples from Parkinson’s patients and healthy study participants. This enabled them to identify 23 proteins that showed differences between the diseased and healthy participants and could therefore be considered biomarkers for the disease.

Secondly, the 23 proteins were examined in the blood samples of people with isolated rapid eye movement (REM) sleep behavior disorder because this represents a high risk for Parkinson’s disease.

The researchers then used AI to identify eight of the 23 proteins that could be used to predict Parkinson’s disease for 79 per cent of these ‘high-risk’ patients up to seven years before the onset of symptoms.

How Will This Help? 

Dr Michael Bartl (a member of the UMG’s Translational Biomarker Research in Neurodegenerative Diseases working group and one of the first authors of the study) highlighted how the research findings will help, saying: “By determining eight proteins in the blood, we can identify potential Parkinson’s patients several years in advance. Drug therapies could be given at an earlier stage, which could possibly slow down the progression of the disease or even prevent it from occurring”. Dr Barl also added “We have not only developed a test, but also make the diagnosis using eight marker proteins that are directly linked to processes such as inflammation and the breakdown of non-functional proteins. These markers also represent potential targets for drug treatments”. 

What Does This Mean For Your Business? 

The development of a simple but AI-enhanced blood test that can indicate Parkinson’s at an early stage (seven years before symptoms) signifies a groundbreaking advancement not only in medical diagnostics but also in the broader application of AI technology.

For businesses, particularly those in the healthcare and biotech sectors, this research highlights the transformative potential of AI in tackling many complex health challenges. The ability to predict Parkinson’s disease so early could lead to earlier interventions, potentially slowing disease progression and improving patient outcomes. This breakthrough demonstrates the crucial role AI can play in early disease detection and personalised medicine, opening new avenues for innovation and investment in healthcare technologies.

For companies operating outside the healthcare sector, the implications are equally important. The research highlights how AI could address significant challenges across various industries, from health and business to climate and environmental management. For example, AI’s capability to analyse vast datasets and identify critical patterns could be leveraged to optimise operations, improve decision-making, and enhance sustainability efforts. Businesses can, therefore, draw inspiration from this study to explore AI applications that could revolutionise their own processes, leading to increased efficiency and competitive advantage.

Also, this development highlights the importance of collaboration between academic institutions and industry. The partnership between UCL and the University Medical Centre Goettingen showcases how interdisciplinary cooperation can lead to significant technological advancements. Businesses should consider fostering similar collaborations to drive innovation and stay at the forefront of technological progress.