Tech Insight : How Fair And Effective Are AI Recruitment Platforms?

With more companies using AI to screen CVs and candidates’ body language during interviews, we look at what this could mean for today’s job applicants.

Widely Used 

IBM research from November last year shows that 4 out of 10 companies now use AI to improve recruiting and human resources. Also, in June last year, IBM highlighted how, with 10 million job openings in the spring of 2023, but only 5.7 million unemployed workers in the U.S., workers would have the advantages in negotiating for higher pay, and better benefits and conditions. It argued that using AI, companies are “reevaluating their recruitment processes”, e.g. to identify inefficiencies and opportunities where AI and automation could make the processes more attractive both for candidates and employees.

What Is AI Used For In Recruitment? 

AI-based systems/platforms, such as HireVue, MyInterview, Retorio, Entelo, Pymetrics, Talview,  and LinkedIn Talent Solution can be used in recruitment, among other things, to:

– Scan CVs and give scores to candidates based AI’s assessment of who is the best match, thereby speeding up and simplifying the initial screening.

– Analysing candidates’ body language, speech, and facial expressions during video interviews to provide insights into the candidate’s personality and suitability for the role.

– Using assessments and games to evaluate candidates’ cognitive abilities, emotional intelligence, and other traits.

– Using predictive analytics to help recruiters understand when candidates are more likely to be open to new opportunities.

– Helping recruiters write job listings that are inclusive and appealing to a diverse range of candidates (Textio).

– Some hiring tools can also assess, based on things like pay and work history, if a candidate or employee is more at risk of resigning.

What Benefits Do These Platforms Provide To Organisations? 

HireVue says that its platform makes hiring faster and fairer, offers security and integrates with an organisation’s applicant tracking system (ATS0) to create a seamless hiring ecosystem. HireVue says that it also offers mobile-friendly, text-powered solutions giving flexibility to both sides of the hiring process.

Other general benefits that AI recruitment platforms offer include:

– Improved efficiency by automating routine tasks, freeing recruiters to focus on strategic interactions.

– Reducing unconscious biases by focusing on relevant criteria, promoting diversity and inclusion.

– Providing valuable insights and analytics to make data-driven decisions about candidates, thereby enabling more strategic talent acquisition.

– Enhancing the candidate experience and ensuring timely communication and engagement, improving the overall candidate journey (according to the platform providers and businesses using them).

– Enabling scalability by efficiently managing a high volume of applications.

– Helping with recruitment planning, e.g. by giving foresight into future hiring needs and workforce trends.

– Reducing recruitment costs by decreasing time-to-hire and automating the screening process.

Do They Work? 

One crucial question for businesses thinking of using the platform is likely to be ‘do they work?’ i.e., how successful are these AI platforms at choosing the right applicant and delivering the right benefits to businesses using them? Some research that could provide an answer include:

– A report (Alight – 2017), showing that companies using AI for recruitment saw a 75 per cent reduction in time-to-hire and a 35 per cent decrease in cost-per-hire.

– A Harvard Business Review (Kuncel, Ones, Klieger) suggesting that AI-driven recruitment tools can increase the quality of hires by up to 50 per cent.

– Deloitte research (2023) showing that organisations using AI-based recruitment tools reported a 20 per cent increase in the diversity of hires.

– A US National Bureau of Economic Research study claiming that companies using AI in their recruitment process can save up to 30 per cent.

What About Applicants? 

Applicants, however, may be less trusting and appreciative of AI-based recruiting and it could feel a little dystopian or uncomfortable to think that your future could be decided in an instant by an algorithm. One well publicised (Sky News) example of a negative experience is that of former MAC make-up artist Anthea Mairoudhiou who took legal action against MAC’s parent company, Estee Lauder, claiming that she’d lost her job due to a low body language score in a HireVue interview.

Other Issues 

In addition to the fact that applicants risk feeling unfairly judged, other key issues that should be considered by companies using the platforms include:

– Bias and fairness, i.e. the risk of AI perpetuating existing biases. How AI has been trained, for example, has led to bias in some models. There are therefore concerns about diversity and equitable treatment where AI is used to judge applicants.

– Transparency and explainability, e.g. a lack of clarity on AI decision-making processes. Companies should ideally provide feedback to rejected candidates.

– Privacy and data security, e.g. legitimate concerns over the usage and storage of personal data. Companies should look carefully at the security and privacy aspects of the AI recruiting platform they use and understand the need for explicit consent and ethical data usage.

– Compliance with legal standards including adherence to anti-discrimination laws and employment regulations. This means that mechanisms to audit AI decisions should be available.

– Candidate experience and human touch. From an applicant’s point of view, it’s helpful to not feel as though there’s an over-reliance on AI in the recruitment process and insofar as feeling as though a company has maintained a personal touch can make a big difference.

It’s also worth noting that companies may need to consider how they will ensure accessibility for all candidates, including those with disabilities, when using AI recruitment platforms.

What Does This Mean For Your Business? 

The adoption of AI recruitment platforms like IBM’s is reported to be reshaping the hiring landscape (perhaps for larger businesses), offering businesses a dual advantage: enhanced efficiency and a more strategic talent acquisition approach. These platforms, by automating routine tasks, can free up recruiters to focus on more nuanced aspects of hiring, promising not only a quicker but a more qualitative recruitment process.

However, using this technology doesn’t come without its challenges. For job seekers, the impersonal nature of AI assessments, as highlighted by Anthea Mairoudhiou’s experience, can be off-putting, underlining the need for a balance between automated efficiency and human touch. Businesses, while enjoying the benefits of AI, must also navigate through issues of bias, transparency, and data privacy, ensuring their recruitment practices are not only efficient but also fair and compliant with legal standards.

In essence, while AI recruitment platforms offer significant benefits around optimising recruitment processes and broadening talent pools, it’s crucial for businesses to integrate these tools with a keen awareness of their potential pitfalls. This means not just leveraging AI for operational efficiency but also addressing the nuanced expectations of job applicants and rigorously adhering to ethical, legal, and privacy standards. The goal is a recruitment process that is not just technologically advanced but also inclusive, fair, and respectful of candidate experiences.

Tech News : Google Maps Gets AI Boost

Google has announced that it is trying out generative AI within Google Maps as a way for users to discover new places based on their questions.


What Google means is that if users, for example, are visiting a town or city, they can simply tell Google Maps what they’re looking for and AI will find it. Google’s large-language models (LLMs) analyse the information in Maps and then make suggestions for where to go based on the user’s question. Google says that the ability to suggest places on the fly using generative AI will benefit users if they are “feeling spontaneous or need to change your plans suddenly.” 


The US-based example given by Google about how it works is: “Let’s say you’re visiting San Francisco and want to plan a few hours of thrifting for unique vintage finds. Just ask Maps what you’re looking for, like ‘places with a vintage vibe in SF.’ Our AI models will analyse Maps’ rich information about nearby businesses and places along with photos, ratings, and reviews from the Maps community to give you trustworthy suggestions.” 

Google says the results are displayed in “helpful categories” 

Experiment – Local Guides First 

Google says that adding generative AI Maps is at the “early access experiment” stage and it is currently being tested in the US among “select Local Guides” (members of its Maps community who give feedback on new Maps products and updates).

Search Updated In October 

This latest “supercharging Maps with generative AI” is the next step onwards from the addition of generative AI to Search in Maps back in October last year. That change meant that the generative AI overlayed photos of what users were looking for on the map. The photos (such as food or realistic pictures of buildings) came from photos shared by users and advanced image recognition models.

Other features introduced at the time also included information about charging stations on routes for EV drivers (Android and iOS) and, in the US, the addition of Lens in Maps. Previously known as Search with Live View, Lens uses AI and AR to show where there are nearby ATMs, restaurants, and more.

What Does This Mean For Your Business? 

Google says the addition of generative AI to Maps is “just the beginning” and it certainly provides incredible scope for adding more layers of value and augmentation of the Maps product.

Google, like Microsoft, has invested heaviy in AI and in December it introduced its “Gemini” model which it described as the “most capable and general model we’ve ever built” and which can understand, operate across, and combine different types of information including text, code, audio, image, and video. Also, like Microsoft, Google is keen to get its generative AI both incorporated into (and adding value to) its suite of products and, crucially, monetise it by packaging it into new products like Gemini Pro and Gemini Ultra.

The AI “supercharged” Maps is likely to provide more new opportunities for Google to expand its advertising revenue. It also highlights the importance, particularly for businesses with premises that attract customers in the local area (e.g., restaurants and shops) of getting plenty of good reviews on their Google business profile. It also shows the importance of keeping this (and their website) up to date with their latest products and services, perhaps making sure they’re mentioned in their reviews so that AI can select their business when a person asks the AI in Maps for a specific product/service in the area. Google is, therefore, using AI to retain and re-engage businesses with its products.

Tech Insight : Copilot Product Update – Some Pros And Cons

Following Microsoft’s recent announcement that it is expanding its Copilot product line-up to appeal to a larger range of businesses, we take a look at what this means and some of the stand-out pros and cons.


In November last year, Microsoft, a major investor in AI through its partnership with OpenAI (ChatGPT’s creators) announced that its long-awaited Copilot AI “companion” was generally available to enterprises. Copilot is essentially Microsoft’s own GenAI chatbot that’s been designed to integrate with the suite of popular apps in Microsoft 365 and uses a variant of the GPT-4 model, specifically tailored and optimised for integration with Microsoft‘s apps.  Microsoft says Copilot: “combines the power of large language models (LLMs) with your data in the Microsoft Graph (API), the Microsoft 365 apps, and the web to turn your words into the most powerful productivity tool on the planet”.

Open AI’s ChatGPT, however, was launched a whole year earlier and started charging for its ChatGPT Plus version in February 2023. At the same time, another major AI player, Google, launched its ‘Bard’ in an effort to integrate advanced AI and language model capabilities into Google’s suite of products and services (like Copilot integrates with Microsoft’s 365 suite of products).

With the major tech companies quickly introducing, monetising and competing with their AI products, what’s Microsoft’s latest move with Copilot?


Microsoft recently announced that it is expanding Copilot for Microsoft 365 “to businesses of all sizes” by adding new ‘Copilot Pro’ subscription for individuals, expanding Copilot for Microsoft 365 availability to SME-sized businesses, and announcing a no-seat minimum for commercial plans. To summarise these developments:

Just as individuals can buy ChatGPT Plus subscription, individuals can now also buy a Copilot Pro subscription for the same amount ($20 per month). Like ChatGPT, Microsoft says Copilot Pro gives access to the latest GPT-4 model at peak times and an AI image tool – in this case ‘Designer’ (formerly Bing Image Creator). Other positives highlighted by Microsoft include commercial-grade data security protection and Copilot embedded in Outlook, Word, Excel, PowerPoint, and OneNote. Users can also build their own Copilot GPT (just as ChatGPT users can build their own tailored chatbots – known as GPTs).

For Businesses 

Most relevant to the focus of this article, however, is what businesses can now get, and how much it’s going to cost.

For example, SMEs can now buy a $30 (£24.70) per person, per month subscription (which may sound a little steep if you’re a small business) for Copilot for Microsoft 365. It’s available to Microsoft 365 Business Standard or Business Premium licence customers. Being targeted at smaller businesses means it has a no-seat minimum and, in line with the idea that all businesses (“individuals, enterprises, and everyone in between”) can use Copilot, up to 300 seats can be purchased. Again, if your business needs a couple of hundred seats worth, and with apparently no free trial or volume discounts, the $30 per user per/month price may be a little daunting.

That said, many businesses are still relatively new to Copilot, may not have leveraged most of its features and, as such, may not have a clear idea of its value to compare to the price. Microsoft is (of course) confident that SMEs “stand to gain the most from this era of generative AI—and Copilot is uniquely suited to meet their needs.” 

Up Front? 

Whereas Microsoft’s subscription services usually offer a choice between monthly or annual payment plans, with the annual plan often providing a saving compared to monthly, there have been reports that the $30 per month is for an annual commitment with payment required upfront. As more information makes it online about user experiences it may soon become clearer if this is the only option for some users.

What You Get 

A Copilot for Microsoft 365 subscription offers users the same as Pro, only with Enterprise-grade security, plus Copilot in Teams (which may be very useful for reviewing the main points, action items, and providing summaries), and Microsoft Graph Grounding. Essentially, it enables work content and context to be added to Microsoft Copilot’s chat capabilities.

Also, customisation through Copilot Studio is possible. This tool enables users to customise and extend the capabilities of their Copilot and to create, customise, and share “skills” or specific tasks that Copilot can perform. In short, the benefit of Copilot Studio is that it enables businesses to tailor the AI’s functionalities to their unique workflows and needs.

What Else? 

Other key points from Microsoft’s announcement include:

– Microsoft is removing the Microsoft 365 prerequisite for Copilot—so now, Office 365 E3 and E5 customers are eligible to purchase.

– The Semantic Index for Copilot to Office 365 users with a paid Copilot license is being extended. Semantic Index works with the Copilot System and the Microsoft Graph to create a map of all the data and content in your organisation, thereby enabling 365 Copilot to deliver “personalised, relevant, and actionable responses”.  

The Word Online 

With this being still the beginning of a generative AI revolution and with much attention being focused on comparisons between leading products such as ChatGPT, there are many opinions online about how Copilot may compare. For example, some commentators point out that Copilot has the benefit of being trained on the huge resources of GitHub, while others say ChatGPT can produce outputs showing it too has been trained on GitHub. Also, some emphasise the value of Copilot being able to get the hang of your codebase, learn your style conventions, and adapt to your suggestions, whereas ChatGPT may be better for inspiration and occasional queries. At the moment, more people have used ChatGPT than have used Copilot for any length of time, so opinions vary.

A Possible Fly In The Ointment? 

Although Microsoft is forging ahead with the expansion, segmentation, and monetisation of Copilot, one possible fly in the ointment may be the outcome of the current antitrust investigation into Microsoft’s close relationship with OpenAI.

What Does This Mean For Your Business? 

Microsoft has invested heavily in AI, mainly through its relationship with OpenAI, and its much-heralded Copilot, its answer to ChatGPT, is now being made generally available to businesses as Copilot for Microsoft 365. This will of course allow it to compete with OpenAI and Google’s AI products and generate some revenue for Microsoft after years of investment.

Microsoft is aiming fairly wide with its “individuals, enterprises, and everyone in between” market to maximise reach, accessibility, and revenue opportunities. However, many of the SMEs that Microsoft says Copilot for 365 will be perfect for may be thinking that the price (and perhaps the requirement to pay a year upfront) is a little daunting, given that many have not yet had any/much experience of Copilot and may be unaware of how much value it may add. That said, Microsoft designed Copilot with the integration into (and leveraging of) its suite of apps in mind, which is where it has the edge over standalone AI offerings. Also, Microsoft and OpenAI’s close (possibly too close) relationship has meant that Microsoft’s AI products are on the cutting edge.

For many small businesses who are already familiar with (and committed to) Microsoft’s products, it’s likely to be a case of looking at the numbers and seeking a little more information, perhaps from their Managed Service Provider, before taking the plunge.

Featured Article : New Certification For Copyright Compliant AI

Following many legal challenges to AI companies about copyrighted content being scraped and used to train their AI models (without consent or payment), a new certification for copyright-compliant AI has been launched.

The Issue 

As highlighted in the recent case of the New York Times suing OpenAI over the alleged training of its AI on New York Times articles without permission for free (with the likelihood of a ‘fair use’ claim in defence), how AI companies train their models is now a big issue.

The organisation ‘Fairly Trained’ says that its new Licensed Model certification is intended to highlight this difference between AI companies who scrape data (and claim fair usage) and AI companies who license it, thereby getting permission and pay for training data (i.e. they choose to do so for ethical and legal reasons). As Fairly Trained’s CEO, Ed Newton-Rex says: “You’ve got a bunch of people who want to use licenced models and you’ve got a bunch of people who are providing those. I didn’t see any way of being able to tell them apart” 

Fairly Trained says it hopes its certification will “reinforce the principle that rights-holder consent is needed for generative AI training.” 

Fairly Trained – The Certification Initiative

The non-profit ‘Fairly Trained’ initiative has introduced a Licensed Model (L) certification for AI providers that can be obtained by (awarded to) any generative AI model that doesn’t use any copyrighted work without a licence.


Fairly Trained says the certification can go to “any company, organisation, or product that makes generative AI models or services available” and meets certain criteria.

The Criteria  

The main criteria for the certification includes:

– The data used for the model(s) must be explicitly provided to the model developer for the purposes of being used as training data, or available under an open license appropriate to the use-case, or in the public domain globally, or fully owned by the model developer.

– There must be a “robust process for conducting due diligence into the training data,” including checks into the rights position of the training data provider.

– There must also be a robust process for keeping records of the training data that was used for each model training.

The Price 

In addition to meeting the criteria, AI companies will also have to pay for their certification. The price is based on an organisation’s annual revenue and ranges from $150 submission fee and $500 annual certification fee for an organisation with a $100k annual revenue to a $500 submission fee and $6,000 annual certification fee for an organisation with a $10M annual revenue.

What If The Company Changes Its Training Data Practices? 

If an organisation acquires the certification and then changes its data practices afterwards (i.e. it no longer meets the criteria), Fairly Trained says it is up to that organisation to inform Fairly Trained of the change, which suggests that there’s no pro-active checking in place. Fairly Trained does, however, say it reserves the right to withdraw certification without reimbursement if “new information comes to light” that shows an organisation no longer meets the criteria.

None Would Meet The Criteria For Text 

Although Fairly Trained accepts that its certification scheme is not an end to the debate over what creator consent should look like, the scheme does appear to have one significant flaw at the moment.

As Fairly Trained’s CEO, Ed Newton-Rex has acknowledged, it’s unlikely that any of the major text generation models could currently get certified because they have been trained upon a large amount of copyrighted work, i.e. even ChatGPT is unlikely to meet the criteria.

The AI companies argue, however, that they have had little choice but to do so because copyright protection seems to cover so many different things including blog and forum posts, photos, code, government documents, and more.


Mr Newton-Rex has been reported as saying he’s hopeful that there will be models (in future) that are trained on a small amount of data and end up being licensed, and that there may also be other alternatives. Examples of some ways AI models could be trained without using copyrighted material (but probably not without consent) include:

– Using open datasets that are explicitly marked for free use, modification, and distribution. These can include government datasets, datasets released by academic institutions, or datasets available through platforms like Kaggle (provided their licenses permit such use).

– Using works that have entered the public domain, meaning copyright no longer applies. This includes many classic literary works, historical documents, and artworks. Generating synthetic data using algorithms. This could include text, images, and other media. Generative models can create new, original images based on certain parameters or styles (but could arguably still allow copyrighted styles to creep in).

– Using crowdsourcing and user contribution, i.e. contributions from users under an open license.

– Using data from sources that have been released under Creative Commons or other licenses that allow for reuse, sometimes with certain conditions (like attribution or non-commercial use).

– Partnering / collaboratiing with artists, musicians, and other creators to generate original content specifically for training the AI. This can also involve contractual agreements where the rights for AI training are clearly defined.

– Using web scraping but with strict filters to only collect data from pages that explicitly indicate the content is freely available or licensed for reuse.

Collaboration and Agreements 

Alternatively, AI companies could choose to partner with artists, musicians, and other creators to generate original content (using contractual agreements) specifically for training the AI. Also, they could choose to Enter into agreements with organisations or individuals to use private or proprietary data, ensuring that the terms of use permit AI training.

What Does This Mean For Your Business? 

It’s possible to see both sides of the argument to a degree. For example, so many things are copyrighted and AI companies such as OpenAI with ChatGPT wouldn’t have been able to create and get a reasonable generative AI chatbot out there if it had to get consent from everyone for everything and pay for all the licenses needed.

On the other hand, it’s understandable that creatives such as artists or journalistic sources such as the New York Times are angry that their output may have been used for free (with no permission) to train an LLM and thereby create the source of its value that it may then charge users for. Although the idea of providing a way to differentiate between AI companies that had paid and acquired permission (i.e. acted ethically for their training content sounds like a fair idea), the fact that the LLMs from the main AI companies (including ChatGPT) may not even meet the criteria does make it sound a little self-defeating and potentially not that useful for the time being.

Also, some would say that relying upon companies to admit when they may have changed their AI training practices and potentially lose the certification they’ve paid for (when Fairly Trained isn’t checking anyway) may also sound as though this may not work. All that said, there are other possible alternatives (as mentioned above) that could require consent and organisations working together that could result in useful, trained LLMs without copyright headaches.

Although the Fairly Trained scheme sounds reasonable, Fairly Trained admits that it’s not a definitive answer to the problem. It’s probably more likely that the outcomes of the many lawsuits will help shape how AI companies act as regards training their LLMs in the near future.

Tech News : Work Starts On £790m UK Google Data Centre

Work has started on Google’s first UK data centre which will cost $1 billion (£790m), will add to Google’s 27 data centres worldwide, and will support its move into AI.

Crucial Compute Capacity 

The data centre is being built on a 33-acre site at Waltham Cross, Hertfordshire. In addition to the construction and technical jobs that Google says the building work will bring to the local community, Google says its investment in the data centre will deliver “crucial compute capacity to businesses across the UK, supporting AI innovation and helping to ensure reliable digital services to Google Cloud customers and Google users in the UK and abroad.” 

Google says that its investment in the technical infrastructure needed to support innovation and tech-led growth in areas like AI-powered technologies is vital, hence the new data centre.

Off-Site Heat Recovery 

Google is also keen to highlight how the data centre’s carbon footprint will be minimised. For example, in addition to the company’s goal to run all its data centres and campuses completely on carbon-free energy (CFE) by 2030, it says the new data centre in Hertfordshire will “have provisions for off-site heat recovery”. 

Data centres produce large amounts of heat and so an off-site heat recovery system is a way for energy conservation that benefits the local community through capturing the heat generated by the data centre and using it in nearby homes and businesses. Google also says the data centre will have an air-based cooling system, presumably rather than a water-based one.

Part Of A Continued UK Investment 

Google has highlighted how the new data centre is part of its continued investment in and commitment to the UK which it says is “a key country for our business and a pioneering world leader in AI, technology and science.”

Other recent Google investments in the UK (in 2022) include:

– A $1bn purchase of our Central Saint Giles office in London’s West End.

– A 1 million sq. ft. Office and local innovation hub in King’s Cross.

– The launch of an Accessibility Discovery Centre in London, aimed at boosting accessible tech in the UK.

Google is also keen to highlight its free digital skills training, offered across the UK since 2015, and the expansion of its Digital Garage training programme in the UK (including a new AI-focussed curriculum).

UK Government Pleased 

Prime Minister Sunak, who’s been keen to woo big tech companies to the UK to support its ambitions to be a major global tech centre, has welcomed Google’s $1 billion data centre investment as an endorsement of this. He also highlighted how such “foreign investment creates jobs and grows all regions of our economy and investments like this will help to drive growth in the decade ahead.”  

Also, UK Chancellor of the Exchequer, Jeremy Hunt, has expressed that he is “delighted to see this investment from Google” and that it ”reflects the success of the UK tech sector, which is now the third largest in the world after the US and China – worth over $1trillion and double the size of anywhere else in Europe.” 

What Does This Mean For Your Business? 

The growth of cloud computing followed by the rapid growth of AI, which has a much bigger demand for computing power, plus the move by competitors into AI (Microsoft has announced an impending £2.5bn to expand data centres for AI across the UK) are key drivers for Google’s new UK data centre investment. The infrastructure is needed to support the AI which will in turn help boost productivity, creativity, and opportunities for UK businesses, and Google’s investment in the UK is good for job creation, boosting the economy, and bolstering the UK’s ambitions for being a tech centre.

However, Google is also reported to have been laying off many workers as it slims down to accommodate AI and, although the immediate community around Waltham Cross may benefit from some low-cost/free heat, there are other matters to bear in mind. For example, AI is an energy and thirsty technology and although there’s an ambition to run its data centres on carbon-free energy (CFE) by 2030, the Waltham Cross data centre should be finished and running by 2025. Like other data centres, it will still require huge amounts of energy (it shouldn’t need water too because it’s to be air-cooled), which is a matter that hasn’t been highlighted in the announcement about the investment so far. The impact on the local grid and environment, and the impact on the environment of the build itself may also be of concern.

That said, work is only just starting, more data centres are needed to fuel our AI-powered future, and there are no other good alternatives to this kind of expansion as yet so for UK businesses, the investment in the UK and its benefits are being welcomed.

Security Stop Press : The Threat Of Sleeper Agents In LLMs

AI company Anthropic has published a research paper highlighting how large language models (LLMs) can be subverted so that at a certain point, they start emitting maliciously crafted source code.

For example, this could involve training a model to write secure code when the prompt states that the year is 2024 but insert exploitable code when the stated year is 2025.

The paper likened the backdoored behaviour to having a kind of “sleeper agent” waiting inside an LLM. With these kinds of backdoors not yet fully understood, the researchers have identified them as a real threat and have highlighted how detecting and removing them is likely to be very challenging.

Sustainability-in-Tech : Google’s AI Discovers 380,000 New Materials

A new AI tool called GNoME from Google’s DeepMind artificial intelligence lab has reportedly discovered and contributed nearly 380,000 new compounds to the Materials Project, the open-access database founded at the Department of Energy’s Lawrence Berkeley National Laboratory (Berkeley Lab).


The Graph Networks for Materials Exploration (GNoME), is an AI-powered deep learning tool and a state-of-the-art graph neural network (GNN) model. Originally trained with data on crystal structures and their stability, it is particularly suited to discovering new crystalline materials.

Why Is Finding New Crystalline Materials So Important? 

As Google’s DeepMind says: “Modern technologies from computer chips and batteries to solar panels rely on inorganic crystals. To enable new technologies, crystals must be stable otherwise they can decompose, and behind each new, stable crystal can be months of painstaking experimentation.” 

380,000 New Stable Materials Discovered  

DeepMind reports that using its GNoME AI model, not only has it discovered 2.2 million new crystals (the equivalent to nearly 800 years’ worth of knowledge) but has identified 380,000 of these as being the most stable, making them promising candidates for experimental synthesis.

Faster And Cheaper Than Past Methods 

As DeepMind has highlighted, the traditional methods of scientists searching for novel crystal structures have been adjusting known crystals or experimenting with new combinations of elements. These methods have proven to be an expensive, trial-and-error processes that could take months to deliver limited results. Using the GNoME AI model, therefore, has dramatically speeded up and reduced the cost of this process.

Work Already Under Way On The New Materials 

Google says that researchers in labs around the world have already independently created 736 of the newly discovered structures as part of experimental work. Also, in partnership with Google DeepMind, researchers at the Lawrence Berkeley National Laboratory have published a paper showing how the AI discoveries can be leveraged for autonomous material synthesis.

What Does This Mean For Your Organisation? 

Many essential modern technologies rely on a supply of stable inorganic crystals, e.g. for computer chips, batteries, and solar panels. However, up until now, old methods of finding these crystals have involved time-consuming and expensive trial-and error process. Having an AI tool like GNoME has dramatically increased the speed and efficiency of discovery by predicting the stability of new materials. In doing so, it has demonstrated the potential of using AI to discover and develop new materials.

This could mean that AI models (such as GNoME) have the potential to develop a range of future transformative technologies which could include superconductors, powering supercomputers, and next-generation batteries to boost the efficiency of electric vehicles. Also, Google DeepMind releasing its database of newly discovered crystals to the research community could reduce development times for these new transformative technologies.

This could benefit society and businesses (new opportunities and new industries) as well as contributing to achieving environmental targets and improving sustainability by accelerating the development green technologies.

Featured Article : What Was Fun At CES?

Following the Consumer Electronics Show (CES) in Las Vegas last week, we take a look at some of the more novel and fun gadgets (and claims from the show) and what lessons businesses can take away from this year’s event.


The Consumer Electronics Show (CES), which this year took place in Las Vegas (from January 9th to 12th) once again acted as a global stage for tech innovation and a glimpse of things to come. It’s a place where industry leaders, startups, and tech enthusiasts converge to showcase and witness the latest advancements and future trends in technology and which sets the tone for the tech industry each year. Among the more ‘serious’ products, however, the show features many fun/novel and more left-field gadgets and claims. Here’s some standout examples of these from CES 2024.

LG’s Smart Home AI Agent. This AI device (a kind of robotic home manager) transcends traditional smart home functions. It’s capable of engaging in meaningful conversations, providing reminders for medication, and even contacting emergency services if needed, showcasing a new level of AI integration in home management. The Smart Home AI Agent is an example of a product that fits LG’s vision of a “zero-labour home”, something that many of us can only dream about!

For those who want to keep their conversations secret, how about Skyted’s Mobility Privacy Mask? This innovative gadget is essentially a Bluetooth-enabled face mask yet it’s designed to absorb voice frequencies, thereby ensuring private conversations in public spaces. The potential applications for the device highlighted by the company include conversations in public spaces, while travelling (for frequent travellers or regular commuters), plus those working in aeroplanes, in and in offices or call centres. It’s an interesting idea which highlights a growing demand for privacy in our increasingly connected world.

GlüxKind’s AI-powered Stroller (Pram), Ella. This gadget is a step forward (or a roll forward) in making the life of modern, connected parents that bit easier. It’s a pram that offers hands-free operation, automatic stopping on inclines, and a gentle rocking feature for the baby. Its built-in white noise machine adds another layer of innovation, showcasing how parenting can be assisted by smart technology.

The WeHead GPT Edition is an AI-powered head with a face that gives ChatGPT a physical form, providing a unique interactive experience. Some have criticised the face for appearing to be a little emotionless when it talks. It’s been designed for brainstorming and idea generation, and it represents an intriguing (some have said creepy) blend of virtual and physical AI interfaces.

Rabbit’s R1 Pocket AI Assistant. Developed by Teenage Engineering, this ($200) handheld AI assistant with a 2.88-inch touchscreen navigates smartphone apps on command, simplifying tasks like ordering food or managing apps. It operates on a language action model, pushing the boundaries of how we interact with our digital devices.

French startup MolluSCAN’s Smart Molluscs is a novel, environmentally-focused technology that uses sensors literally upon molluscs to monitor water quality and pollution. It represents a highly innovative approach to environmental monitoring, combining biology with technology.

For those who remember how some TVs used to fold into cabinets and be disguised as home furniture, SEED’s N1 Folding TV takes things quite a few steps further. This innovative TV transitions itself from a large 137-inch screen to a sleek sculpture. The seamless MicroLED panels provide an uninterrupted viewing experience, reflecting the fusion of technology and art.

On the subject of TVs, how about one you can’t see at all? Samsung’s Transparent TV can blend in with the background of your room when not in use, so it looks like a transparent piece of glass in a frame! The design uses Micro LED technology which Samsung says makes “the line between content and reality virtually indistinguishable.”

In the health industry, ADAM-X by Medical-X is essentially a robot patient that simulates a wide range of medical scenarios and reacts how a live patient would react, providing real-time feedback to trainees. It also has simulated bodily fluids. This advanced CPR dummy is designed for medical training and is a good example of how technology is enhancing medical training with lifelike simulations.

Again, in the health domain, the BMind AI-Powered Smart Mirror by Baracoda is a smart mirror that acts as a mental wellness health companion. For example, this mirror not only reflects your image but also gauges your mood using AI. It can engage in conversations, provide meditation exercises, and even offers light therapy, marking a new era in personal wellness technology.

The Clicks Technology’s BlackBerry-style iPhone Keyboard attachment transforms an iPhone into a device reminiscent of the BlackBerry era. It provides a tactile typing experience while liberating screen space, blending nostalgia with modern smartphone functionality.

Sound Drive’s Dynamic Sound Mixing, created by’s startup, is a system that adjusts your car’s music based on your driving speed and conditions. It dynamically mixes the music, adding or dropping lyrics as needed, to match the energy of your drive.

How about having a conversation with your bathroom furniture? A step too far? Not in the case of Kohler’s PureWash E930 Bidet Seat which features voice command capabilities. It allows users to control various functions such as activating the spray or dryer, or using its self-cleaning UV feature, all through voice commands with Alexa or Google Assistant. Just be careful not to say the wrong thing at the wrong time!

One novel piece of tech for pets presented at CES this year was the ‘Flappie,’ the AI-powered cat flap, described as “world’s most intelligent” cat flap.  Flappie uses cameras and AI to prevent unwanted visitors from following your pet indoors. It’s designed to recognise your cat and distinguish it from other animals, ensuring that only your pet has access. This product reflects the increasing use of AI in everyday household items, offering convenience and problem-solving in unexpected areas.

What Does This Mean For Your Business?

It seems that CES 2024 has demonstrated how technology is becoming increasingly intertwined with every aspect of our lives. From smart-home advancements to groundbreaking developments in environmental monitoring and healthcare, even the more novel tech innovations offer a glimpse into a future where technology enhances and simplifies our daily experiences.

For UK businesses, these trends underscore the importance of embracing innovation, focusing on user experience, and exploring eco-friendly technologies. They also highlight how the integration of AI is changing everything and opening up so many more opportunities and avenues for product innovation and enhancement. The gadgets and AI advancements from CES 2024, therefore, not only reflect the current state of technology but also offer a roadmap for future developments. UK businesses can learn from these innovations to identify new opportunities, meet emerging consumer needs, and stay competitive in a rapidly evolving global tech landscape.

Although this selection focuses on the more novel and unusual gadgets, the key general takeaway from CES 2024 could be that the future is not just about technology for its own sake, but technology that enriches, simplifies, and adds value to our everyday lives.

Tech Tip – Use ChatGPT Within Microsoft Word

The ‘Add-Ins’ link on the menu (top-right) in Microsoft Word in Office 365 enables you to use many useful apps and tools directly within Word, including ChatGPT. Here’s how it works:

Open a Word document and click on ‘Add-Ins’ (a grid symbol) top-right in the horizontal menu bar at the top of the page.

From the dropdown of options, select ‘ChatGPT for Excel and Word’ and follow the very brief instructions to set it up.

Write your document and use the ChatGPT add-in, which appears in the right pane, to research details which you can copy directly into your document using the ‘Copy’ or ‘Insert’ button provided.

Featured Article : ChatGPT Inside Vehicles Opens Possibilities

Following the news that Volkswagen (VW) is to add ChatGPT to the IDA voice assistant in its cars and SUVs, we look at what this could mean for the direction of technology for cars.

Adding ChatGPT 

At the current CET in Las Vegas, VW announced that starting in Europe in the second quarter of this year, the famous chatbot will be added to a variety of VW EVs, including the D.7, ID.4, ID.5 and ID.3, Tiguan, Passat, and Golf.

Drivers will be able to use ChatGPT hands-free via VW’s existing onboard IDA voice assistant, with Cerence Chat Pro from technology partner Cerence Inc acting as the foundation of the new function, which VW says, “offers a uniquely intelligent, automotive-grade ChatGPT integration.”

Within Limits 

It’s been reported, however, that certain limits have been placed on the kinds of questions that VW’s ChatGPT will answer, e.g. no profanity or ‘sensitive’ topics (it’s a family car).


VW’s newsroom says the ChatGPT integration will mean that: “The IDA voice assistant can be used to control the infotainment, navigation, and air conditioning, or to answer general knowledge questions.” Also, VW envisions that: “In the future, AI will provide additional information in response to questions that go beyond this as part of its continuously expanding capabilities. This can be helpful on many levels during a car journey: Enriching conversations, clearing up questions, interacting in intuitive language, receiving vehicle-specific information, and much more – purely hands-free.” 

Just The Start 

Stefan Ortmanns, CEO of Cerence, the company tasked with the integration of ChatGPT with the onboard voice assistant has indicated that this is just the beginning, and that VW looks likely to ramp-up the power of its onboard AI going forward. For example, Ortmanns says: “As we look to the future, together Volkswagen and Cerence will explore collaboration to design a new, large-language-model-based (LLM) user experience as the foundation of Volkswagen’s next-generation in-car assistant.” 

What If It Was Combined With Autonomous Vehicles? 

This first for a volume car manufacturer and commitment to integrating generative AI with vehicles, coupled with the recent UK government suggestion that autonomous cars could be on our roads by 2026 raises some tantalising possibilities and questions. For example, what if AI chatbots like ChatGPT were integrated into autonomous vehicles and how could this affect the evolution of our cars and our commuting experience? Let’s explore some of the potential impacts and transformations this could bring.

Transformation into Access-Pods? 

Cars could evolve from traditional vehicles into “access-pods” and become spaces not just for travel but for various activities. In an autonomous vehicle, the need for a driver is eliminated, which would allow for the interior to be redesigned. For example, seats could become more like comfortable office chairs, and the inclusion of small tables or workstations could become standard. This could transform the car into a mobile office or a personal lounge, making the journey itself a productive or leisurely part of the day.

Working During Commute 

With autonomous vehicles, people could start working during their commute, just as they do on the train (only in a more personal setting). This could significantly change daily schedules, allowing for more flexible work hours. Also, as travel time becomes working time, the distinction between office and home could blur, perhaps leading to a more fluid work-life integration.

Could It Lead To A Societal Shift In Work Habits? 

The ability to work from a private car might lead to changes in living patterns. People might be more willing to live further from their workplaces if they can be productive during longer commutes. This could also have a wider impact on the property market, with less emphasis on living close to urban centres.

Enhanced Productivity and Entertainment 

The integration of AI chatbots in cars (whether autonomous or not) could, as VW suggests, make a journey more interactive and informative. Passengers can engage in productive tasks like setting up meetings, conducting research, or learning new skills through conversational AI. Additionally, entertainment options could become more personalised and interactive.

Safety and Accessibility 

For people who are unable to drive due to various reasons such as age, disability, or other factors, autonomous vehicles with AI integration could offer new levels of independence and mobility.

Traffic and Environmental Impact 

If autonomous vehicles and AI lead to smoother traffic flow and more efficient travel, there could be positive environmental impacts. However, if it encourages longer commutes, it might have the opposite effect.

Regulatory and Ethical Considerations 

With these possible advancements would come the need for new regulations and ethical guidelines, particularly concerning data privacy, cybersecurity, and liability in the event of accidents.

New Business Models?

The prospect of generative AI-controlled autonomous vehicles could also lead to new business models. For example, this could include things like subscription-based access to luxury autonomous pods for commuting, or services that combine transportation with other amenities like fitness, relaxation, or entertainment.

What Does This Mean For Your Business? 

Although VW’s integration of generative AI with vehicle voice assistants is a first for a volume car manufacturer, there was a kind of inevitability to it and it’s unlikely to take long for other car manufacturers to announce the same (they’re probably already working on it). For VW, it’s (currently) a value-adding and differentiating introduction, so provided that the restrictions on what the onboard ChatGPT can discuss aren’t too strict, it could make the driving time much more interesting, productive, and a much more personalised experience. Linking it to the sat-nav for example, may also be a feature that motorists really value, as may be the greater feeling of control, reassurance, and novelty of having something that can tell you about the car and its performance and issues. It may also provide a societal purpose and make people feel less alone while driving and perhaps more alert. Using hands-free voice commands to operate more aspects of the car (e.g. the radio, the hands-free phone etc), may also improve driver safety.

Looking ahead, perhaps to the integration of generative AI with autonomous vehicles, it’s possible that a societal shift could occur where our vehicles become more like productive and comfortable access-pods, which could have wider implications for our work/life balance and business models and could have knock-on effects for whole industries. It could even open new business and entertainment opportunities focused on access-pod occupants. This move by Volkswagen, therefore, offers us a glimpse of a better future for our personal transport options.