The managing director of tech, media, and telecoms for Google UKI has been awarded both an MBE and an OBE for her troubles.

During Black History Month in the UK, Kingori spoke to her fellow Google Alum, Ramat Tejani, at Black Tech Fest about leadership, navigating change, and fostering inclusion in a constantly evolving AI-driven era.

“People mourning the way things used to be will get left behind, 100%” she warned.

From high fashion to high-tech

Transitioning from the world of high fashion to the world of tech is no small feat. In her conversation with Tejani, Kingori described the experience as empowering.

When asked about transferable skills between the two industries, Kingori remarked that both industries demand constant learning and adaptation.

She noted that while she brings a wealth of experience from publishing, she remains in a deep learning phase within the tech world — a trait that all leaders today must embrace.

“Leaders normally show up with a deep knowledge bank from rising through an organisation or industry ranks. But today, we have to lead through change and admit that we don’t know everything,” she said.

Kingori emphasised that leadership now requires humility and collaboration.

She likened this to her time during the rise of social media at Conde Nast when seasoned executives were unfamiliar with emerging platforms like Instagram, and younger, less experienced team members had to step in as experts.

“Try to speak to someone over 35 about TikTok and see what happens!” she exclaimed.

In the tech world, Kingori uses the same approach, empowering her team to share their expertise where hers falls short.

“I see that it makes other leaders nervous, but if I don’t know something, I’m going to empower and uplift my team. I’ll say, ‘You’re the expert on this. Let’s pool our knowledge and create something really collaborative’.”

Navigating change in the AI era

A key theme during the conversation was how leaders should manage change, particularly as AI continues to reshape industries.

Kingori encouraged the audience to adopt a mindset that welcomes change, understanding that disruption creates opportunities for those willing to innovate.

“You can go almost anywhere in the world, and Coca-Cola is the same. We are conditioned to like standardisation, but the world is shifting. Jobs will exist in the future that we don’t even understand yet.”

She continued: “Social media managers didn’t exist before. Now, it’s a key role, and a whole industry has been created around it. So, what will be next?”

While much of the public dialogue surrounding AI focuses on the potential loss of jobs, Kingori encouraged the audience to think about the jobs that will be created, urging them to explore where new opportunities will arise.

“People with ultimate power over things will need to diffuse that power to capture the entire opportunity. It’s about getting into the mindset of letting some things go, learning, and figuring out paths to success rather than mourning what was.

“The people mourning the way things used to be will get left behind, 100%.”

Inclusion in AI: a new frontier?

While there is significant discussion around the risks of bias in AI, Kingori highlighted the potential for AI to be a force for good if deployed thoughtfully.

“There are questions around inclusion that we’ve been trying to crack for decades. Human beings are full of bias, and AI has the power to be led by that bias or to be a neutralising force,” she said.

“I think that there are huge gains that can be made when AI is deployed much more around fairness, especially in these new roles that will be created.”

She referenced Google DeepMind’s AlphaFold, an AI system that recently won a Nobel Prize for solving a complex “50-year-old” scientific problem around protein folding.

Kingori argued that AI has the potential to similarly “solve” long-standing issues of inclusion if marginalised groups are actively involved in shaping these technologies.

“We have this opportunity to kind of “AlphaFold” the inclusion conundrum. The caveat is that we, as marginalised groups, must be in these spaces,” she said.

Kingori was optimistic that AI could help break down some biases inherent in human decision-making, particularly in hiring and organisational structures.

However, she issued a call to action to those from underrepresented communities.

“If we want AI to be part of the solution around problems that organisations face with inclusion, then where we have roles in these organisations, we need to show up,” she stressed.

“Because then you are, in your own small way, shaping what the technology looks like and who it sees, and those things actually matter.”

Storytelling through data and creativity

Coming from a background in publishing, Kingori understands the power of stories, but she now finds herself in a world dominated by data and algorithms.

Rather than viewing these as oppositional forces, Kingori sees them as complementary, highlighting the importance of blending data with emotional resonance to create impactful narratives.

“It’s like linking the head and the heart. The idea that the two exist separately is wrong. Your heart won’t function if your brain doesn’t, and vice versa. The magic happens when we link them.”

AI, she argued, is a tool that can help tell better stories, but human intuition and creativity will always be necessary to bring data-driven insights to life.

It’s not about replacing one with the other but integrating both to achieve more effective communication.

“I don’t think it’s a zero-sum game. It’s not one or the other, in my view,” she concluded.

Key takeaways

The conversation ended on an optimistic note, tempered with caution. Kingori’s advice to tech leaders could be summarised in four points.

Embrace the unknown; leaders should be comfortable with uncertainty and empower their teams to collaborate.

Prioritise mindset over knowledge, fearing change is going to hold you back. Instead, it should be viewed as an opportunity for growth.

Harness the power of AI to boost inclusion. Marginalised voices must be part of the development of AI software to ensure the technology serves everyone fairly.

And finally, effective communication in the age of AI requires a mix of data-driven insights and human-centred storytelling.

Read more about Black Tech Fest adding some seasoning to the scene here.

The post Google’s Vanessa Kingori on leadership, change, and inclusion in the AI era appeared first on TechInformed.

Throughout the Paris Games, Orange ran a private 5G network throughout the city, providing capacity across 32 spots and 120 official sites across the region.

Speaking at a media event in London last week Bruno Zerbib, the company’s executive vice president and CTIO, and Laurent Leboucher, the firm’s group technology officer and senior VP of Orange’s innovation division, said they now had a “unique experience” on how to make workable, scalable 5G private networks a reality.

“We’re going to spend a lot of time sharing over the next few months how we made the games in Paris work,  and how we became the telco that has the most unique experience in making 5G at scale a reality and how we are going to turn it into a product-based offering,” said Zerbib.

“We had to secure broadcast quality service within the 5G network, and we used all those advanced capabilities to make that work with tons of visitors who were using the network at the same time while protecting these very important streams,” he added.

Orange used a “standalone” version of 5G (5G SA) during the Paris Games which enabled it to leverage network slicing capabilities for this dedicated use case, guaranteeing performance on this virtual slice.

Leboucher added that the French telco was now able to offer customers “different flavours” of 5G private networks – to provide more flexibility and cost efficiency for the end user.

“Up to now we used to deploy dedicated 5G networks for stadiums and so on. But because we’ve invested in 5G SA now we can reduce the network cost  and slice it and to create efficiency. We  are starting to do this in Belgium, and Spain and soon we will do it in France,” he added.

According to Leboucher, Orange will soon be able to not just build a dedicated solution for enterprise customers on a project basis, but it will be able to transform this capacity into “a platform that can be leveraged as a service capable of combining both the scale of the public network and the ability to use the private infrastructure and architecture. The best of both worlds,” he added.

Agile all the way

Since Zerbib’s appointment last year, the French telco has consciously moved away from the traditional linear progression of the mobile generational model (4G, 5G, 6G etc) choosing instead to  act more like  hyperscalers such as Amazon or Google, offering clients capabilities, products and services through platforms or APIs.

In part, this is a reflection of what is happening within the wider industry, with mobile providers collaborating with the developer community on API integrations through projects such as CAMERA , Open Gateway,  and, more recently, last month’s joint venture spearheaded by Ericsson and a dozen or so telecom operators (including Orange) to scale their offerings and sell their APIs globally.

Zerbib, who worked in Silicon Valley for 25 years at Big Tech firms including HP, Cisco and Yahoo –  reiterated this approach, adding that it was essential that the telco rolled out new capabilities on the software side more frequently.

“Through the power of [the Ericsson] joint venture we can enable the system in a unified way with  one API and code to scale globally.

“It [the Ericsson JV] will also enable other developer platforms and hyperscaler developers by exposing the capabilities of our network. We want to build solutions that add value.”

Zerbib added that the industry needed to avoid fragmentation when it came to APIs, to make sure they were universal “so that we don’t create a lock up situation for customers.”

While Orange’s CTIO said that the company would take a use case-led approach, this translated into fewer actual examples than you might think,  although Leboucher did highlight fraud prevention as one popular application of telco APIs- which is backed up by GSMA research.

Augmenting networks with AI

The rise of generative AI and automation is something that Zerbib believes will compliment this agile approach. Internally, Zerbib revealed that AI has made Orange a better company. The firm has trained 40,000 employees to use its AI capabilities to increase operational efficiencies, he revealed.

One use case, the French exec added, would be using LLMs to map the layout of an enterprise’s entire network. The model could understand and anticipate customer support requirements and effectively become an engineer offering appropriate solutions.

Bringing it back to 5G private networks, Zerbib talked about fully automated and virtualised 5G networks that operate through AI – and hinted that the transformational 5G experience that telcos have long been espousing, will finally be realised through AI augmentation.

How the firm best goes about creating these LLMs is where Orange finds itself today, the CTIO admitted, adding that the telco was currently reviewing its options.

Zerbib and Leboucher do not currently think that Orange will need to build an LLM from scratch – nor one that was telco specific – especially when a series of generic “Vanilla AIs” were working well for some applications.

Generic LLMs – such as Chat GPT (which French exec Zerbib referred to as a “she”), Google’s Gemini, Facebook’s Llama and France’s Mistral have all  been good enough so far for network applications such as summarising tickets and alerts that technical staff investigate, Zerbib claimed.

The Orange execs added that the costs of training LLMs from scratch were currently too high -but a more cost friendly and equally effective option might be “fine tuning”  some of these existing LLMs.

Zerbib also hinted that processing power to train LLMs may require some telco expertise.

“There is going to be a need for some edge computing, where you have something in the middle,” Zerbib said. “Processing would happen not on the device or in a huge data centre but in smaller facilities of the kind Orange uses for its network

The post Orange to productise Olympics 5G offering – and reveals LLM approach appeared first on TechInformed.

For many CISOs who have take the ‘zero failure tolerance’ approach, this advice from Gartner VPs – Akif Khan and Christopher Mixter – during the influential analyst firm’s annual Risk and Security Summit – must have felt counter intuitive.

The analyst duo told leaders that in an ever-expanding landscape, firms needed to start writing off annual losses because of cyber-attacks and ransomware.

“Retail stores accept a certain amount of loss due to shoplifting. Banks accept a certain amount due to the fraud because they know that stopping these things entirely would be completely cost prohibitive,” reasoned Khan.

“Organisations and their leaders have well developed thresholds for fault tolerance everywhere. Everywhere that is accept cybersecurity. Why are organisations ok about being ripped off by 3% of revenue due to fraud but think it’s completely impossible to experience any losses due to a cyber attack?” he asked delegates.

According to Mixter, preventing every single attack from happening was simply cost prohibitive. “We could spend 10 times what we do today on preventing cyber-attacks and still every organisation in this room would be massively exposed.”

The analysts argued that zero tolerance was also leading to burnout among staff. “Our zero tolerance kicks in and we say, ‘not on my watch’. But that’s a major source of burnout because heroism is exhausting,” said Khan.

“We need to break this hero mentality and one of the best ways to do that is talk about what kind of impact you can tolerate. Work backwards and think of the level of investment,” he advised

IR playbook for GenAI

In the conference’s opening keynote, Gartner unveiled the concept of “Augmented Cybersecurity,” advising leaders to shift away from zero tolerance mindset and engage in response and recovery capabilities.

Mixter called this “resilience through intention rather than resilience through adrenaline.” The analysts suggested that firms start by building incident response (IR) playbooks around two areas that are already coming under constant attack.

The first was Generative AI – an area, said Khan, where it was impossible to prevent attacks from occurring 100% of the time. “Therefore, your ability to adapt, and respond and recover from the inevitable issues becomes critical for your organisation to explore Gen AI successfully.

For the Gartner analysts, start by building an IR handbook which asks questions like: ‘If our data is not AI-ready due to quality issues how much information are we willing to tolerate?’ Especially for critical apps like an AI chatbots.

“Can you swap it out for a different AI alternative application? What’s the switching costs? The most crucial question: can we pull the plug and recover business operations if something goes horribly wrong – for instance – How do we react if our chatbot decides to give customers unwarranted refunds?” Khan suggested.

While some may say that hand-holding an organisation though its GenAI efforts may create even more work for an overstretched cyber team, Mixter claimed it presents a unique opportunity for CISOs to lead an organisation and demonstrate how strong response and recovery was “the only way to succeed in the face of an ever-evolving technology like Gen AI,” he maintained.

Gartner also predicted that by 2026 AI security applications would increase the efficiency of security operation centres by 40%.

“Rather than replacing existing tools, AI augments them by presenting it with issues that make it easy for non security staff to understand and take action – explainability, risk assessments and noise reduction all help to make sure the right issues are being prioritised while keeping distractions to a minimum,” Mixter observed.

He added that the next wave of Gen AI would create augmented agents “that observe user tasks and workloads but unlike chatbots where you to talk to them, the AI augment talks to you – reducing workloads and speeding up decision making…” he added.

Gartner predicts that these augments will help “collapse the cyber security skills gap” by 2028, removing the need for specialised education for up to half of all of entry level cyber security positions.

Third party supply chain

The firm also highlighted third party risk from vendors, recommending that organisations have a formal third-party contingency plan, including an exit strategy when or if an incident occurs with a vendor.

Recent incidents such as the global CrowdStrike outage have highlighted the impact third-party systems can have on businesses.

“Augmented cyber security means building out these lines of defence to make it as easy as possible to manage third party risk exposure… and put those plans in practice by conducting third party incident response plans.

“We tabletop lots of things, surely its time we added third party tabletop exercises to our roster?” said Mixter.

Such a plan, he added could lead to a 43% improvement in effectiveness of third-party cyber risk management.

Elsewhere, Gartner also advised that firms further consolidate their toolsets and create an inventory of what an organisation already must see where tech stacks can be streamlined – something the firm first suggested at the same conference last year.

On the show floor meanwhile, vendors had mixed views on Gartner’s keynote messaging.

Danny Jenkins, founder and CEO of Zero Trust cyber firm ThreatLocker pointed out that in some sectors, once a breach has occurred, the irreversible damage has already been done.

“You can’t recover when your data has been extracted. The idea that you can recover from a cyber attack is rubbish.

“What happens when someone takes six terabytes of your confidential files? How do you recover from that? Once it’s out you can’t get it back.

“It doesn’t matter how good your IR is if you are a hospital or if you are Boeing and all your aircraft designs go out to your rivals – that’s unrecoverable you can’t transfer that risk and insure yourself against a market cap loss,” he told TI.

“The idea you should be investing in response and not in detection is crazy. Of course, you want to have an IR plan, but this plan should never have to be used. I’ve got fire extinguishers in my home and smoke detectors, but I’d rather not leave the pan on the hob when I go out.

“The best response should be never having to execute it. There are so many attacks and that’s why zero trust is so important. It’s impossible to detect every single attack – but if you harden and make your system more controlled than the attacks can’t happen.”

Nicholas McKenzie, CIO and CISO of bug bounty platform Bugcrowd meanwhile, said that while a consolidation of tools made sense, protective security controls and preventive controls should still be the priority.

“Both from an operation and cost perspective consolidation of security tools are forefront and centre of everyone’s agenda.”

“However, accepting that there’s a risk and being effectively breached and responding all the time is a vastly different mentality. If you keep responding and recovering to attacks, you are going to have to keep pooling more and more resources into responding versus stopping them at the gate.”

The post Gartner: CISOs should ditch ‘zero tolerance’ prevention and focus on response & recovery appeared first on TechInformed.

Occurring just a couple of weeks after the global CrowdStrike IT outage, which ground airports to a halt and forced medical facilities to resort to pen and paper, it felt the right time to reflect as firms find themselves under pressure to adopt AI  faster and release products before they are properly evaluated.

Lisa Einstein, senior AI advisor at the US Cybersecurity and Infrastructure Security Agency (CISA), compared what she called “the AI gold rush” to previous generations of software vulnerabilities that were shipped to market without security in mind.

“We see people not being fully clear about how security implications are brought in. With the CrowdStrike incident, no malicious actors were involved, but there was a failure in the design and implementation that impacted people globally.

“We need the developers of these systems to treat safety, security and reliability as a core business priority,” she added.

The Internet Security Alliance’s (ISA) president and CEO, Larry Clinton, put it more bluntly: “Speed kills — today we’re all about getting the product to market quickly — and that’s a recipe for disaster in terms of AI.”

He added: “Fundamentally, we need to reorientate the whole business model of IT, which is ‘Get to market quick and patch’. We need to move to a ‘Secure by Design’ model and to work with government partners so we are competitive and secure.”

Many of the event’s sessions, which featured speakers from WTT, Microsoft, CISA, Nvidia, as well as the CIA’s first chief technology officer, were focussed on how organisations might achieve ‘Secure by Design’ AI, which TechInformed has summarised in eight key takeaways.

1. Do the basics and do them well

“You can’t forget the basics,” stressed veteran CIA agent Bob Flores during one of the event’s panel sessions. “You have to test systems and applications and the connections between the applications, and you have to understand what your environment looks like,” he added.

Flores, who, towards the end of his CIA career, spent three years as the agency’s first enterprise chief technology officer, asked Black Hat’s AI conference delegates: “How many of you out there have machines that are attached to the internet that you don’t know about? Everyone’s got one, right?”

He also warned that, with AI, understanding what’s in your network needs to happen fast “because the bad guys are getting faster. They can overcome everything you put in place.”

And while enterprises might think it’s safer to develop their own LLMs rather than to rely on internet-accessible chatbots such as ChatGPT, Flores is concerned that they might not be building in security from the beginning. “It’s still an afterthought. As you build these LLMs, you must think, every step of the way, like a bad guy and wonder if you can get into this thing and exploit it.”

2. Architect it out

Bartley Richardson, cybersecurity AI lead at GPU giant NVIDIA, advised the Black Hat crowd to look at AI safety from an engineering perspective.

“When you put together an LLM application, don’t just look at every block you’ve architected there; look at the connections between those blocks and ask: ‘Am I doing the best possible security at each of those stages?’ ‘Is my model encrypted at rest?’ Are you putting safeguards in place for your prompt injections?’ This is all Security by Design. When you architect it out, these things become apparent, and you have these feedback loops where you need to put in security,” he explained.

3. Create a safe space to experiment

Matt Martin, founder of US cyber consulting firm Two Candlesticks and an AI Security Council member for Black Hat, advised that creating a controlled sandbox environment within which employees can experiment was important. “A lot of people want to use AI, but they don’t know what they want to do with it just yet – so giving them a safe space to do that can mitigate risk,” he said.

Martin added that it was important to understand the business context and how it was going to be applied. “Ensure someone in the company is in overall control of the projects. Otherwise, you’ll end up with 15 different AI projects that you can’t actually control and don’t have the budget for.”

4. Red team your products  

Brandon Dixon, AI partner strategist at Microsoft, explained how the software giant is balancing advances in AI with security. “We’ve done that through the formation of a deployment safety board that looks at every GenAI feature that we’ve deployed and attaching a red teaming process to it before it reaches our customers,” he says.

Red teaming is an attack technique used in cybersecurity to test how an organisation would respond to a genuine cyber-attack.

Check out our healthcare cybersecurity tabletop coverage here

“We’ve also formed very comprehensive guidance around responsible AI both internally and externally, consulting experts, which has enabled us to balance moving very quickly from the product side in a way that doesn’t surprise customers,” he added.

5. Partnerships are paramount

According to CISA’s Lisa Einstein, ‘Secure by Design’ relies on public and private enterprise partnerships. She added that this is particularly important in terms of sectors that provide critical infrastructure.

To this end, in 2021, CISA established the Joint Cyber Defense Collaborative (JCDC). This public-private partnership aims to reduce cyber risk to the nation by combining the capabilities of the federal government with private sector innovation and insight.

Einstein told conference delegates: “CISA only succeeds through partnerships because more than 80% of critical infrastructure is in the private sector in the US.

“We have a collective and shared responsibility. I’m seeing organisations that didn’t think they were part of this ecosystem, not realising that they have part of the responsibility. Tech providers also need to help these enterprises become more secure and keep everything safe,” she said.

Partnerships with and between vendors were also emphasised at the event. Jim Kavanaugh, longtime CEO and technology guru of $20 billion IT powerhouse World Wide Technology, spoke on the benefits of the firm’s long-term partnership with chipmaker Nvidia, including advances with AI.

In March this year, WWT committed $500 million over the next three years to spur AI development and customer adoption. The investment includes a new AI-proving ground lab environment and a collaboration ecosystem that uses tools from partners, including Nvidia.

While former CIA agent Flores recognised that such partnerships were crucial,  he also stressed the need for firms to conduct robust assessments before onboarding.

“Every one of your vendors is a partner for success, but there are also vulnerabilities. They must be able to secure their systems, and you must be able to secure yours. And together, you must secure whatever links them,” he noted.

6. Appoint an AI officer

The conference noted the rise of the chief AI officer, who oversees the safe implementation of AI in organisations. This appointment is now mandatory for some US government agencies following the Biden Administration’s Executive Order on the Safe, Secure and Trustworthy Development and Use of AI.

These execs are required to evaluate different ways to deploy robust processes for evaluating use cases and AI governance.

While it was not a requirement for CISA to appoint a chief AI officer, Lisa Einstein stepped up to the role last month as the organisation recognised that it was important to its mission beyond having an internal AI use case lead.

“CISA wanted someone responsible for coordinating those efforts to ensure we were all going in the same direction with a technically sound perspective and to make sure that the work we’re doing internally and the advice we are giving externally is aligned so that we can adapt and be nimble, “she explained.

While this doesn’t have to be a board-level appointment, Einstein added that the person needs to be in the room with an ever-expanding roster of C-Suit players: the CIO, the CSO, the legal and privacy teams, and the data officers when decisions and policies on AI are made.

Einstein added that, within ten years, the position should be redundant if she’s done her job well. “By then, what we do should be so ingrained in us that we won’t need the role anymore. It would be like employing a chief electricity officer. Everyone understands the role they must play and their shared responsibility for securing AI systems and using them responsibly.”

7. Weave AI into your business operations

For ISA chief Larry Clinton, Secure by Design starts with theory. For over a decade, his organisation has collaborated with the US National Association of Corporate Directors (NACD), the US Departments of Homeland Security, and the Board of Direct Justice on an annual handbook for corporate boards to analyse cyber risk.

According to Clinton, ISA is currently developing a version of this handbook specifically for working with AI, which will be released this fall.

Clinton claimed that enterprises need to bring three core issues to the board level.

“AI deployment needs to be done strategically. Organisations underestimate risks associated with AI and overestimate the ability of staff to manage those risks. This comes from an idiosyncratic adaptation of AI, which needs to be woven into the full process of business operations, not just added on independently to various projects,” he says.

The second issue, he said, was education and the need to explain AI impacts to board members rather than explaining the nuts and bolts of how various AI deployments work.

The third issue, he added, was communication. “It’s critical that we move AI out of the IT bubble and make it part of the entire organisation. This is exactly the same advice we give with respect to cybersecurity. AI is an enterprise-wide function, not an IT function.”

8. Limiting functionality mitigates risk

According to Microsoft’s Brandon Dixon, limiting the actions that an AI system is capable of is well within a human’s control and should, at times, be acted upon. The computer giant has done this with many of its first-generation copilot tools, he added.

“What we’ve implemented today is a lot of ‘read-only’ operations. There aren’t a lot of AI systems that are automatically acting on behalf of the user to isolate systems. And I think that’s an important distinction to make — because risk comes in when AI automatically does things that a human might do when it may not be fully informed. If it’s just reading and providing summaries and explaining results, these can be very useful and low-risk functions.”

According to Dixon, the next stage will be to examine “how we go from assertive agency to partial autonomy to high autonomy to full autonomy. At each one of those levels, we need to ask what safety systems and security considerations we need to have to ensure that we don’t introduce unnecessary risk.”

The post Black Hat USA 2024: Eight ways to achieve ‘Secure by Design’ AI appeared first on TechInformed.

According to Mike Capone, CEO of data analytics giant Qlik, success in AI begins and ends with data mastery: “Today, with the unlimited computing power and advances in generative AI available, we have the ability to spit out garbage at a breathtaking rate,” he warned.

Capone spoke in Florida last week at Qlik Connect, a gathering of industry leaders and developers from the vendor’s vast customer base. The key message at the event was the critical need to implement AI ethically and responsibly.

He explained that data quality determines any future ability to harness value from AI and analytics but recognised that managing data quality is one of the key challenges that his customers face and one that was preventing many of them from scaling AI use cases.

Capone underscored his point with a recent McKinsey survey that found over 70% of leading organisations said that managing data was one of their top growth inhibitors.

Establishing AI governance

How can businesses adopt AI responsibly? According to Meredith Whalen, chief research officer at market analyst IDC, who spoke at the event, companies can start by establishing an AI governance framework to help them balance pursuing new AI technologies with responsible development.

Whalen also suggested forming an AI council composed of diverse experts to provide guidance and develop practices for model transparency and data integrity.

“Our data shows that organisations are focused right now on model transparency guidelines and data integrity practices. That’s important because transparency and explainability are going to build trust among your users and among your stakeholders,” she said.

Whalen also highlighted the importance of regular employee training on ethics and responsible AI use, especially regarding security, which she recognises as everybody’s responsibility.

AI councils assemble

What are AI councils? Internally, it transpires that Qlik is hot on AI councils, essentially a group of diverse experts that provide guidance on AI implementation, focusing on model transparency and data integrity.

A council can also help ensure that AI development aligns with ethical standards and builds trust among users and stakeholders.

Tech entrepreneur and proclaimed AI expert Nina Schick, a member of Qlik’s very own AI Council, suggested that an AI council could also help verify AI-generated content to guarantee its integrity.

This kind of body could also facilitate discussions between industry and government to establish policies that balance innovation with fairness and societal impact.

According to Schick, AI councils can also bring together experts from various sectors to discuss AI’s future and identify necessary actions to promote responsible development and adoption.

Emphasising that computing power and data are the two essential resources driving the AI revolution, Schick believes that while computing power has increased exponentially, data is now the “new oil” that powers AI.

She argued that companies must optimise, codify, and consolidate their data to build sovereign AI and own the production of their proprietary intelligence. Schick claimed this would be critical to success in the age of AI: “All companies of the future, in my view, will be AI-first companies who build their sovereign AI.”

Implementing AI: 5 practical stages

The consensus at Qlik Connect around implementing AI responsibly and effectively boiled down to five practical steps.

The first involves assuring data Integration and quality control. To maintain high quality, all data needs to be integrated, transformed, and governed. Businesses also need to consolidate data from diverse sources, ensuring its integrity through rigorous quality control measures.

Only with high-quality data can AI yield reliable results. As Mayer said: “You can’t have an AI strategy without having a good data strategy.”

The second step is to form an AI council (as mentioned previously) to develop transparency and data integrity practices and provide regular ethics training for employees.

Understanding data provenance and maintaining rigorous governance are crucial. Transparency builds trust among users and stakeholders, who know that the data driving AI decisions is well-vetted.

The third step is to foster transparency and accountability, using metrics to build trust in AI systems. Equitable access to comprehensive, trusted data is essential. All stakeholders should rely on the same data pool to ensure consistency and reliability in AI outcomes. As Capone said: “You need access to complete and trusted data for everybody.”

Adopting an agile approach was the fourth key learning from this event. Companies need to ensure that they continuously learn and adapt policies as AI technology evolves.

This includes experimenting with new techniques while maintaining alignment with ethical and market needs.

“If you are in an organisation that’s risk-averse or hesitant to get started because you’re concerned about the risks of AI, the biggest risk is to do nothing. Your competition is out there experimenting,” warns IDC’s Whalen.

The final piece of advice, more of a prediction, comes from Qlik’s VP of market readiness, Martin Tombs. He suggested focusing on AI for specific business applications rather than generic AI models. These models, he added, will need to be validated continuously to build trust over time.

“Achieving trust in unstructured data is about keeping your blast radius short and focussing on your business. I predict we will start with more generic LLMs and then evolve into domain-specific LLMs. There’ll be ones specific to call centres, support teams, salespeople, etc. And trust will come when it’s an accurate answer.”

The post Trust in AI: getting your house in order appeared first on TechInformed.

Now the UK has entered the election campaign period there was little promise of any major policy announcements on the first day of the tech event’s 11^th anniversary, which this year moves to a new venue – Olympia, on the edge of London’s Kensington.

With most of the conference stages swathed around stands and booths, the event is starting to resemble the outline found at most other tech shows, with stands taken by IBM, Unilever as well as hordes of nations promoting start-ups and investment opportunities.

London didn’t need a stand, however, as it had Khan who used his opener to promote the city’s self-appointed status as a tech superhub.

“Our city is one of the largest and most influential tech centres on the planet,” he enthused. “We boast more than 100 unicorns; we are home to more software developers than any other European city.

“The big names from Google to Microsoft are expanding their operations here with investments that are making London a global hub for AI and innovation. “

Khan added that London’s unashamedly “pro-business pro-tech” stance, would inform the capital’s new growth plans, which he said would have “AI and innovation” at their core and would aims to create 150,000 new jobs in London over the next four years.

Self driving unicorn

This year’s TechNation report, UK Tech In the Age of AI – released on the first day of the show – revealed that the city now has 171 tech unicorns (start-ups worth over £1bn) which were all created within the last three years.

Another of the report’s top lines was the fact that the UK is now the number one destination in Europe for AI investment, with the UK AI sector reaching a combined market valuation of $92bn in the first quarter of 2024.

Encouragingly, more scale ups are also now choosing to remain in the country to seek further investment – including Wayve, a self driving, AI powered start up founded in 2017 by New Zealand-born Cambridge graduate Alex Kendall.

The entrepreneur followed Khan onto the stage, to talk about opportunities in the next big thing: embodied AI. His tech firm recently raised $1bn in funding from Japan’s Softbank alongside California chipmaker Nvidia and Microsoft to invest in embodied AI for automated driving in the UK.

Kendall explained that embodied AI would enable automated vehicles to learn from and interact with a real-world environment, including the ability to learn from situations that do not follow strict patterns or rules, such as unexpected actions by drivers or pedestrians.

The entrepreneur added that the UK’s newly approved Autonomous Vehicles Act  – which will make it legal to run autonomous vehicles on British roads as soon as 2026 – meant that the tech firm would not be caught up in the broader sweeping AI legislation coming out of the UK and EU, because it’s now governed by these more domain-specific rules.

While the UK Government has claimed victory over the Wayve investment (the biggest yet for a UK-founded AI-start up) and has been supportive legislation wise –Kendall added that there was still more work to be done in terms of nurturing and supporting deep tech companies.

“In terms of scale up capital in the UK there is still an incompressible cycle time. With deep tech in particular – the depth of expertise and the risk taking is just not there. It will come – and can be built on early success stories – but it is not there yet.

The founder added that continued investment in the scale up ecosystem was needed – and not just for fintech and SaaS start-ups – but in more deep tech companies.

“Government policy can influence things with tax and regulatory structures – but it’s about giving the ecosystem time to grow,” he added.

Natwest’s Cora + launches

IBM’s UK CEO Nicola Hobson introduced two of its enterprise partners onto the stage, to demonstrate how firms have been “seizing the AI opportunity.”

First up was Wendy Redshaw, chief digital information officer at NatWest Retail Bank, who unveiled the new Gen-AI infused version of their customer service digital assistant, Cora+ which had launched that morning.

The previous version of Cora, introduced in 2017, has already helped the bank’s customers with over 10m online banking queries in 2023 (compared to 5m in 2019).

Cora + incorporates both generative AI – using multiple foundational models from IBM, Meta and Open AI – as well as traditional AI – so that customers can have a more natural conversational engagement with the bank.

Redshaw explained: “For example, previously when a customer asked for a mortgage or a lending product, a link would be provided to a general page and the customer would scroll through and navigate different options. The customer would have to do some of the work.

“Cora+ will be able to understand the context and nuances of each query the customer makes and can provide accurate and personalised responses,” she added.

Getting ahead in advertising

Media agency WPP’s chief technology officer Stephan Pretorius was next up, predicting that “AI and Gen AI would transform every part of the knowledge work that we do today” from strategy and consulting to law to marketing and ad production.

According to Pretorius, achieving the benefits of AI starts with leadership: “Never before in my career have CEOs been so focussed on one topic across all industries. It requires all our business leaders to have vision of how AI can be acquired and to drive that through the organisation and industry,” he said.

The CTO added that an AI strategy also required a focus on partnership with tech firms like IBM, “to be able to integrate with multiple third-party technologies and data.”

Another key factor was investment, Pretorius added, as he revealed WPP now invests 2% of its net sales revenue in AI investment.

Embracing AI also involved transforming the workforce “at every level,” he added: “The UK has incredible talent pools, but you must transform the people you have as well as bringing in new skills. We’ve sent a large cohort of people to do AI post graduate diplomas and invest in our people.”

WPP’s creative Technology Apprenticeship, he said, was focussed on hiring young people from diverse backgrounds that were “disproportionately female” so that they could develop AI skills in a body of staff that was“ more representative of the word we live in.”

According to Pretorius, WPP has amassed at least 50 Gen AI applications across its advertising business – from helping to generate concepts, creating storyboarding videos with Text-to-Video as well as creating content for products that don’t exist yet, to stimulate early-stage demand.

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As I was expertly shepherded into the event’s keynote at London’s Excel Centre, the army of new and experienced cloud user delegates (many of whom are software developers) was impressive, although slightly less so was the gender ratio – which I’d estimate as one woman to every seven men, despite Amazon’s best efforts to improve the pipeline in this region.

It will come as no surprise to learn that artificial intelligence was the summit’s main theme, with keynote speaker Tanuja Randery who is AWS’s VP and managing director of EMEA, announcing that the UK economy is sitting on the brink of a £520bn opportunity in accelerating AI adoption by 2030, according to a recent Amazon report.

Naturally, the vendor is offering some tools to assist with the unlocking of these business opportunities. Among one of the first announcements at the event was news that the hyperscaler’s GenAI offering, Amazon Bedrock, has now launched in the UK.

First unveiled last year, AWS’s Bedrock service includes an all-you-can-eat menu of gen AI models from Amazon as well as other third-party partners, including AI21 Labs, Anthropic, Cohere, Mistral AI, Stability AI and Meta Llama – all offered through an API.

Bedrock also allows users to build apps on top of generative AI models and customise them with their own proprietary data and, as of yesterday, with their own proprietary AIs.

Another stalwart the vendor is keen to push is its SageMaker product, a managed service in AWS public cloud. This tool is not new – it was released in 2017 – but it provides the tools to build, train and deploy machine learning models for predictive analytics application. Many early GenAI innovations have seen this tool used in tandem with Bedrock.

Dentsu and Lonely Planet

Several enterprise use cases in GenAI highlighted how firms can increase their bottom line using these technologies. Randery pointed to Amazon’s partnership with global ad firm Dentsu, which is adopting SageMaker and Bedrock to scale its genAI use.

In Brazil one of Dentsu’s clients, Nissin Foods, used the tools to enable a campaign to achieve 109% increase in year-on-year sales and to boost social engagements by 21 million.

In Portugal, Randery added that Dentsu was able to launch an easy reading app to over 40 million people with learning difficulties.

Fellow keynote speaker Francessca Vasquez, AWS VP of professional services and GenAI Innovation Centre, also revealed that guidebook brand Lonely Planet was developing GenAI with tools to help people plan incredible trips and customise their itineraries.

“They are using Anthropic’s quad model, through Amazon Bedrock, and as a result they have reduced itinerary generation costs by nearly 80%,” she said.

Tui: from inspiration to destination

Sticking with the theme of travel, leisure group Tui’s CIO and guest keynote speaker Pieter Jordaan revealed how the firm was using AI to make the most of its petabytes of data.

“We needed to break the norm to go big with cloud and AI. To give you the scale of what we’re trying to achieve we’re taking the equivalent of the entire population of Australia (over 21m) away on holiday every year,” said the CIO.

Tui has partnered with AWS for seven years as part of its digital transformation journey, Jordaan added, and is using data in the cloud – and now AI – to “redefine personalised travel experiences”.

According to Jordaan, during the pandemic, rather that scale down IT operations Tui decided to capitalise on this unexpected downtime and “go big and to go all in on AWS”.

This involved building a cloud-native platform and globally migrating its call centres to Amazon Connect to improve the customer experience –a move he claims that has reduced agent handling time by 20%.

“We transformed our IT organisation into a globally distributed workforce and have now trained 90% of our IT staff on AWS skills. And now we’re in the process of training them on generative AI,” he said.

Expedia: opening the data treasure trove with gen AI and LLMs

Post-Covid, the strategy has been to lean in and focus on creating curated personalised travel experiences, which AI has enabled them to do, Jordaan maintained.

“The move to the cloud native platform allowed us to accelerate and embrace AI. We increased our model deployment in Amazon SageMaker by 1000% in one year,” he claimed.

Last year, the CIO launched Tui’s own AI Lab to drive generative AI adoption through the entire organisation – generating use cases from board level to the flight staff to the travel reps in the resort.

One of the biggest challenges in this area was to find use cases that delivered measurable value, Jordaan admitted.

His solution for this was to use AWS PartyRock – a tool that can be used within Bedrock as a kind of ‘AI playground’ to make foundational models with AIs from Amazon and other leading AI companies.

“We used PartyRock to work backwards and coach to train the teams to really produce clear and measurable problem statements so that we could quickly protype ideas,” Jordaan explained.

Site-seeing

One such use case to emerge was content generation. At any one time the travel group has 100,000s of holidays on sale and they all need inspirational content. Yet to create SEO to scale that matches the tone-of-voice of the brand and is also personalised s a huge challenge, the CIO noted.

“And yet, from a business perspective, even if we achieve just a 1% point move in online organic traffic with better content, this is the equivalent of 8.5m Euros in cost,” he calculated.

“The team was already familiar with SageMaker and Llama and we were able to use Bedrock to manage our foundation models and enhance our SEO content beyond just the travel facts, and really personalise with a tone-of-voice that matches the experience,” he said.

Of Bedrock he added: “By utilising model stacking we could solve a problem that we couldn’t solve with a single model.

“We first used Llama2 to create the content and then we would pass it to [Anthropic’s] Claude 2 to do alignment on tone of voice, and then we moved onto the fine tuning for the languages.

He added that in GenAI multiple model choice is becoming important: “that ability to quickly iterate over new models whether that’s inspirational search or cutting our call centre time in half.”

Another product in its AI armoury is AWS’s gen AI-powered chatbot for called Q, which has been trained on 17 years of AWS data, making it useful to help build web applications.

Jordaan added that Tui was now in the process of rolling out Amazon Q developer to over 2000 of its engineers to improve efficiency.

From Zilch to $2bn

Another speaker, this time from the world of fintech, was Philip Belamant – CEO and cofounder of London-based Zilch, a buy-now, pay-later unicorn, currently valued at $2bn.

Explaining the company’s unique business model Belamant said: “In the UK we are paying $150 a year on fees and interest on credit. We wanted to drive this sum to zero – or zilch – for customers by introducing brands directly to buyers at the point of payment and using ad budgets to subsidise the credit process.

“So, a customer buys a pair of shoes. We underwrite the customer in real time for an affordable line of credit.  We then package up that intent and share it with our ad partners and what they allow brands to do is programmatically bid in real time on that BNPL sale.

“The customer takes out a line of credit and pays zero interest and zero fees of any kind and Zilch is still able to operate this at a 50% + profit margin. This is what we’re calling the world’s first ad subsidise payments network. We’re currently doing 3,000 transactions of these every second and climbing.”

Cloud native

Infrastructure wise, Zilch was born on AWS Cloud says Belamant, and the firm has been scaling the company the cloud ever since. At the event the CEO announced “a deepening in its collaboration” with the vendor focussing on AI.

Bud Financial: using AI and LLMs to drive bankable insights

According to Belamant, the fintech uses AI across four lines: fraud, credit, customer serving and buyer intent prediction. Touching on two of these areas he says:

“If you look at credit underwriting this is fundamental to our business. Our team would take weeks to build a new underwriting model and then test that model and deploy it. Today with SageMaker we can do all of this within just days.

“And here’s the interesting part: we are currently ingesting more than ten times the data for that model than we used today. Initial tests are showing that the predictability of this model is now almost twice as predictive as it used to be. And we’re just getting started.

The second area the fintech entrepreneur enlarged on was intent prediction: “This is critical: A customer tells us where they like to shop. What is interesting is what if you knew where you were going before you told us? And one day what if we knew what was valuable to you before even you knew? So, we’re going to be combining GenAI and ML to serve this up.

He explains: “We understand what the customer might need or view as valuable, we feed it to gen AI through Bedrock and various models and then we serve this in natural language or a really rich content way – it could be images – this will transform content as we know it.”

Belamant claims that Zilch has already saved customers half a billion dollars in fees and interest, adding “if we get this right, we may have the most credible way of eliminating the high cost of consumer credit for good.”

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The advocacy group for London’s private tech sector, which boasts more than 18,000 members, together with the tech campus Here East, claims that the eight policy focus areas will drive growth and prosperity of the capital’s tech ecosystem.

Announced at a TLA event today at Here East’s campus on the Queen Elizabeth Olympic Park, areas of focus included upskilling Londoners with AI and LLM skills, the funding of more locally-based green tech ventures as well as pushing more initiatives that will make the London Stock market a more attractive listing location for scale-ups.

The tech association also recommended making 5G more of a London-wide rather than a Central London-only feature, as well as improving diversity and inclusion throughout the sector with skills bootcamps and other programmes.

Tech London Advocates & Global Tech Advocates founder Russ Shaw said that the recommendations were designed “to strengthen London’s vibrant tech ecosystem as a launchpad for the future, ensuring the city retains its place as a world-leading tech hub”.

He added: “Improvements to diversity of talent in the sector and the need to build ultra-fast fibre networks are not wishful thinking, but basic requirements to fuel the continued growth of London tech.”

Incumbent Mayor of London, Labour’s Sadiq Khan, is the favourite to win a third, four-year term as London Mayor. Khan’s green pledges include a zero-emissions bus fleet by 2030, along with 40,000 electric vehicle charging points in the capital.

Khan also recently called for a crackdown on disinformation leading up to the mayoral elections, following a deepfake audio of his voice which was widely distributed on social media.

Other candidates include the Conservative’s Susan Hall, who is focussed on female safety in the city, and independent candidates such as Natalie Campbell – the co-CEO of bottled water social enterprise Belu.

The eight recommendations – in full

According to TLA and Here East the following policy areas should be considered over the next four-year term:

Develop and revitalise London’s digital talent Expand the Mayor’s pledge to equip Londoners with the skills necessary to take full advantage of a new AI and LLM-driven tech environment by investing in upskilling and reskilling programmes, as well as London’s world-leading universities, ensuring the capital has access to the world’s most digitally literate workforce.

Support a balanced and effective regulatory landscape Support the CMA and CFA in creating an agile regulatory environment that encourages innovation but protects against the dangers of untested emerging technologies; support the building of regulatory sandboxes and create a regulatory framework that can quickly adjust to a rapidly changing tech ecosystem.

Bolster London’s ‘world-leading’ cleantech sector Position the cleantech sector as one of the first lines of defence against the climate emergency. Create educational programmes that inspire the next generation of cleantech enthusiasts, while demonstrating its real-world potential by supporting green technology and clean air initiatives throughout the city, building on the mayor’s pledge for a greener London.

Make the London markets a more attractive place to list Strengthen London’s listing environment by adopting pro-business initiatives that encourage UK-based businesses to scale at home. Create an entrepreneur-led environment by removing needless bureaucracy and supporting pro-business reforms such as the Mansion House Compact.

Harness London’s capabilities with emerging technologies Develop world-leading emerging technology capabilities by amplifying the expertise of leading industry groups. Promote existing initiatives such as the London Data Charter and the Smart London Agenda and build knowledge-sharing bridges between academia and industry.

Improve tech sector diversity and inclusion Champion initiatives that teach technical skills throughout London, ensuring that marginalised groups and those from underrepresented areas can access tech opportunities through skills bootcamps and other skills-focused programmes.

Connect London with other tech hubs – both domestic and international Take advantage of London’s global credentials by enhancing engagement with the wider UK and the rest of the world through trade missions and increased support for major tech events such as London Tech Week and London Data Week.

Build world-beating 5G and ultra-fast fast fibre networks Build on the Mayor’s pledge to make London the world’s best-connected city, building 5G-supporting infrastructure, installing citywide, rather than Zone One focused, super-fast broadband and ensuring continued funding for the ‘Connected London’ scheme. 

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The annual event, which takes place at the Fira Gran Via in Barcelona, had always been a distant buzz of activity beyond my daily routine when I lived there. But now, it was the stage for my deep dive into the world of telecoms and technology.

My colleagues had one piece of advice: “Wear comfortable shoes.” They weren’t kidding. The Fira was an expansive tech jungle — but rather than trees and tigers, I was surrounded by VR headsets and robot dogs.

Walking from one side of the Fira to the other was a feat unto itself, although somewhat sweetened by the Android Partner Walk, a fun little game that involved collecting different Android pins from 16 stands scattered across the 8 halls — collecting all 32 won you a prize, apparently.

Connectivity: beyond wifi and private 5G

The buzz around wifi and private 5G at MWC24 was impossible to ignore — unless you were walking past SK Telecoms’ giant flying “urban drone.” Yet a deeper narrative rustled under the surface for anyone willing to hear.

“Connectivity is not just about faster speeds or broader coverage. It’s about making those advancements accessible and meaningful,” said Panch Chandrasekaran, head and director of the 5G Carrier Infrastructure Segment at ARM.

This sentiment was echoed, albeit with a hint of caution, by Udo Schneider, Trend Micro’s GRS lead and security evangelist. He added, “While we chase the future, let’s not forget the security lessons of the past.”

The dialogue around connectivity wasn’t just a tech debate; it was a reflection on how we ground innovation, making sure it’s secure, sustainable, and, above all, serves a purpose.

Chandrasekaran’s words indicated a shift towards integrated solutions, where the amalgamation of CPUs, GPUs, and accelerators promises to redefine our approach to connectivity and data processing.

Sustainability: the clean energy transition

As tech enthusiasts and leaders, we’re often so focused on the digital that we forget the physical world around us.

Barcelona’s water shortage, a silent plea for conservation echoed throughout the venue (and on the MWC24 mobile app), served as a stark reminder of our environmental responsibilities.

“We’re not just integrating technology; we’re integrating sustainability into our core,” Simay Akar from AK Energy Consulting passionately stated.

A passionate advocate for clean energy and senior member of the IEEE, Akar emphasised the critical role of technology in achieving sustainable development goals.

Our conversation spanned the gamut from solar energy technologies to the electrification of transportation, painting a picture of a future where green cities and smart infrastructure harmonise with the environment.

The conversations at MWC24 weren’t just about the next big thing in tech but also about ensuring that this ‘big thing’ contributes positively to our planet — or so help us all!

Inclusivity: AI as a catalyst for change

At a conference centred around connectivity, it was uplifting to see a genuine interest in connecting everyone. The potential of AI to foster inclusivity emerged as a compelling theme.

“AI for inclusivity isn’t just a nice-to-have; it’s a must-have,” Yo-en Chin, a creative technologist from Deloitte Digital, told me.

Our conversation revealed how AI could be leveraged to enhance experiences for neurodiverse individuals in the workplace and beyond.

The sentiment carried through in many of the people I spoke to, including Sarit Assaf. The general manager at Amdocs spoke of how AI could be the great leveller, giving everyone access to data that was previously reserved for a privileged few, opening doors for marginalised groups.

Collaboration: the key to unlocking potential

Ensuring inclusivity across the board ensures one thing: collaboration. The importance of collaboration in driving technological advancement is unmistakable.

One message reiterated over and over was that the future is built on the foundation of cooperative effort.

This was particularly evident in discussions around the deployment of IoT and critical infrastructure, where the collective endeavour of governments, corporations, and innovators is paving the way for secure, efficient, and accessible technology solutions.

One of the most thought-provoking sessions was “The European Dilemma: Digital Situations, Aspirations, and Rising Challenges.”

The CEOs of Orange, Deutsche Telekom, Telefonica, and Vodafone didn’t just share a stage; they shared a call to arms for the industry.

The consensus was that Europe is at a crossroads, and collaboration, innovation, and a reimagined regulatory landscape are the keys to unlocking its digital potential.

“When we work together, we do pretty cool stuff,” one remarked, capturing the spirit of MWC24.

Grounding our gaze

I guess the biggest takeaway from my first encounter with the MWC beast is that technology isn’t just about devices; connectivity isn’t just about radio waves.

From the discussions on connectivity and security to the urgent calls for sustainability and inclusivity, the conference was a testament to the power of collaboration.

The future of tech is not just about innovation; it’s about making that innovation meaningful, accessible, and, above all, responsible.

And although I didn’t complete the Android bingo, I do now have a lovely collection of pins that I’m sure I’ll find some use for before 6G rolls out.

For more great stories and event roundups like this, click here! And watch Ricki’s roundup video below.

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While the engineering brains behind Apple’s first two computers might still be on Apple’s payroll, it’s been in a ceremonial capacity since he stepped down in 1985.

The 7,000-strong crowd, however, were in for an illuminating retrospective tour of his illustrious engineering career as Woz delivered the closing keynote to Sweden’s largest tech event, which, the organisers revealed, was put together in just six months.

As its ambassador, Apple’s history according to Wozniak, is certainly different to the one audience will have seen through the lens of the Danny Boyle-directed 2015 biopic, on his cofounder, Steve Jobs.

There doesn’t appear to be much love lost between Wozinak and his late friend – whom he became close with when they both worked at HP – but there’s no bitterness there either, even when he delivers such gems as this:

“Steve would go off and say something and you’d assume that it came from him, but often you’d find that came from somewhere else. There was a lot of that.”

He credits Jobs as being the business brains behind the operation but also sings the praises of Apple’s lesser known third cofounder, the business angel Mike Markkula who bankrolled the first 1,000 Apple II computers and whom they relied on for marketing nous and practical advice.

Just kids

“He was the adult in the room,” Wozniak recalled. “He told us: ‘Don’t hire kids’ – even though we were kids – hire people who’ve had success in their chosen fields.”

Yet the idea was never really to start a company, Woz told the event’s chief interviewer, journalist and comms specialist Linda Nyberg, “it was to get my engineering seen by the world.”

Once the duo convinced Markkula to back them, Woz explained how they dined out on the same commercially successful computer model, the Apple II, for ten years.

“Do companies like Apple come from engineering or business and vision? Well, we became a big Fortune 100-based company just on one product. Jobs would tell us ‘We got to have new computers!’  but he didn’t understand computer hardware and software,” Wozniak said.

Wozniak also recalls selling his stock to five founder employees of Apple – something Jobs famously refused to do. “There were us three of us founders with infinite income for life and there were these other people there from the start – so then I also sold other parts of my stock to everybody working for the company.”

Woz is not a tech billionaire. He claims to have given away most of his fortune to various charities and museums (including the Bay Area city he was born in, San Jose, which named the road ‘Woz Way’ after him “that’s something money just can’t buy!”).

At present, Wozniak spends time teaching in schools for free and, while he’s reported to have a few hundred million in the bank, he claimed that he still needs to earn a living, which includes carrying out public speaking at events around the world “over 100 a year, I’m always on planes”.

Dull AI

Wozniak isn’t that impressed with buzzy generative AI, even though Apple is currently rumoured to be secretly building a gen AI division.

“Who needs that much information?  If you want to figure out how to solve problem at work, you go to your search engine you get your results from and figure out how to write a piece of Linux code or whatever.

“But if you go to AI and it just comes back with more spelled out results and strategies for something that you want to do and it sounds so smart – but the trouble is that it’s boring, often there’s just too much to read.”

According to Woz, other AI-generated reports are just dull because they are devoid of emotion, given that AI can only relate to emotions as other humans have expressed them. For this reason, he finds it hard to see how firms can rely on AI alone to make decisions.

“People have to have an emotional reason to make a decision,” he reasoned.

He recounted a story about a professor in Nashville who allows his students to use AI to help them with their papers.

“He’s never given more than a C+ to one because they are just not that good. The human needs to be the editor,” he added.

“The AI is like a ton of reporters bringing the information in, but you need a human to condense it to work out what matters the most. And to express it to someone else in a way that is sellable. Even in your company.”

In terms of AI bias, Wozniak warned that it might be hard to programme against it.

“We’re told we must programme against the biases. But biases are cultures and cultures do matter depending on where you are. You can’t have one AI that is attentive to all the cultures.”

On a practical note, Wozniak proposed taking a ‘scientific journal’ approach to AI-generated content.

“You need to say when something has been AI-generated but there’s also a need for tags so you can click on parts of it to get it to show you what part of networks it was trained on what question it was asked to bring that answer.

“Scientific journals have attribution numbers, and you build science this way.  AI should be no different You should be able to click on any statement so that you know where it came from.”

Photonic computing

One nascent technology that does excite him (“and I’ve been on this one track for 20 years”) is optical computing or photonic computing.

This technology uses light waves produced by visible laser light or infrared (IR) beams instead of electric currents to process data.

An electric current flow at only about 10% of the speed of light, but by applying visible light and/or IR networks at the device and component scale, a computer might one day be developed that can perform operations ten or more times faster than a classical computer.

“Electrons do not go at the speed of light, but photons do,” he explained,

However, he acknowledges that building the technology is a complex process: “What you need is a way to amplify a beam and invert it. And you need a logic gate so that two signals go in and two come out.”

It also requires larger chips, he added, meaning current optical prototypes are bulky.

Why do we need these computers? This all ties into Apple’s and Wozniak’s original vision of creating faster processors that are accessible to everyone to create new photorealistic worlds and new ways of working.

“We are not there yet. We need to improve the bandwidth of the internet and processing ability to handle the kinds of worlds that are coming. We need faster processing: that’s been key my whole life.”

Read how fellow Tech Arena speaker and Apple board member Al Gore thinks technologists can support the crusade to net zero here

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