Agata Karkosz, Leader at FPAcademy at Future Processing

AI is becoming increasingly influential across various sectors and industries. And its impact is only expected to grow in the future. In fact, AI adoption has more than doubled since 2017, with businesses making larger investments to scale and fast-track development.

With such rapid advancements taking place, it is important to educate consumers about navigating the complexities of the technology.

The Current Landscape of AI Education

There are several companies actively providing education and training in the field of AI. Google AI has been offering AI and machine learning courses to consumers for a few years now, while lesser-known companies, like Coursera, edX and Fast.ai, have also entered the space.

Nevertheless, these offerings are often catered to people interested in learning and developing skills in the technology, rather than the everyday consumer. In fact, research released last year by leading software development company, Future Processing, found that more than two-thirds of UK consumers aged 50 and above felt technology companies needed to do more to help them understand AI.

Respondents were asked what AI applications and tools they are currently using, with AI voice assistants and customer service chatbots coming out on top. But, because the technology’s capabilities are wide-reaching, companies need to up their game to ensure the average consumer is in the know.

Educational Initiatives: Are They Enough?

Companies must work harder to help consumers of varying levels of technical expertise understand AI. Doing so will help demystify AI and build consumer confidence and trust.

Understanding this need, Google AI offers resources such as the “Machine Learning Crash Course”, a free online course designed to introduce individuals to machine learning concepts. Microsoft, too, has its AI School, an online platform supplying free courses and resources covering various AI topics, while other major firms, including Facebook, Intel, Amazon and NVIDIA, have sparked similar education initiatives.

Still, due to fresh technological advancements and research breakthroughs, as well as increased data availability, open source and collaboration efforts, rapid industry adoption, and greater funding and investment, the challenge for companies comes in maintaining up-to-date and readily available education materials.

The Challenge of Simplifying Complexity

The inherent complexity of AI arises from the interdisciplinary nature of the field, combining elements of computer science, mathematics, statistics, neuroscience, and engineering. AI involves complex algorithms, sophisticated mathematical models, and intricate programming structures that are hard to rationalise.

Balancing the need to simplify AI concepts for broader understanding while retaining the essential information poses a significant communication challenge for businesses. Oversimplifying may lead to misconceptions or a lack of appreciation for the complexities involved while providing too much detail can result in confusion.

Successful communication often involves using relatable metaphors, real-world examples, and interactive experiences to engage consumers and help them grasp the fundamental principles without getting lost in technical intricacies. Effective communication about AI requires collaboration between experts, educators, communicators, and the general public to ensure a more informed and inclusive understanding of this rapidly advancing field.

Transparency and Explainability

Enhancing transparency and explainability in AI systems has become a key focus for technology companies to address concerns related to bias, accountability, and trust. Several efforts have been made to make AI systems more understandable and interpretable. Some common strategies and initiatives include:

Interpretable Models

Many technology companies are working on developing AI models that are inherently more interpretable. This involves using algorithms and architectures that produce results that can be easily explained and understood. For example, decision trees, rule-based systems, and linear models are often more interpretable than complex deep neural networks.

Explainable AI (XAI) Techniques

Explainable AI is a research area focused on developing techniques and tools that help users understand the decisions made by AI models. Techniques such as feature importance analysis, saliency maps, and attention mechanisms aim to highlight the factors influencing the model’s predictions.

Ethical AI Guidelines

Many companies have established ethical AI guidelines and principles prioritising transparency and fairness. These guidelines may include commitments to avoiding biased data, providing clear explanations for decisions, and involving diverse perspectives in the development process.

User-Friendly Interfaces

Technology companies are investing in user-friendly interfaces that allow users to interact with AI systems more intuitively to enhance transparency. Dashboards, visualisations, and plain-language explanations help users understand the model’s behaviour and outputs.

Addressing Challenges and Gaps

AI education faces several challenges that stem from the diverse nature of the field, the varied backgrounds of learners, and the evolving landscape of information dissemination.

The rapid evolution of AI is a primary challenge, but a lack of standardisation, diverse audience backgrounds, and the spread of misinformation have also hampered the public’s ability to understand the technology.

The highest concerns surrounding AI are privacy, transparency and security. This is supported by Future Processing’s research, with respondents aged 50 and above ranking security and data privacy as their highest concerns when using AI, followed closely by misinformation and question misinterpretation.

But, through ongoing collaboration and dialogue, governments can establish standards which foster diversity and inclusivity, provide up-to-date resources, and emphasise practical application to deliver more effective and equitable AI education.

The Role of Ethical Guidelines

With AI frequently coming under the spotlight, technology companies are increasingly recognising the importance of ethical guidelines and policies in AI development and usage.

Many have published official documents outlining their ethical principles and values concerning AI. These documents typically cover commitments to fairness, transparency, accountability, privacy, and avoiding biases in AI systems. For example, Google and Microsoft’s respective AI Principles are publicly available documents that articulate the companies’ ethical commitments.

Learning to Embrace

Continuous efforts in AI consumer education are imperative to navigate the evolving landscape of AI, bridge educational gaps, address ethical considerations, and ensure that individuals are equipped with the knowledge and skills needed in an increasingly AI-driven world. The commitment to transparency, inclusivity, and ethical practices will contribute to building a more informed and responsible AI community, meaning we can embrace all it can bring to the table, rather than dwelling on its shortcomings.

By Alexia Pedersen, VP EMEA at O’Reilly 

The UK government has made clear its intentions to make the UK a global AI superpower. Key to this is the National AI Strategy, which aims to boost enterprise use of AI, attract international investment and develop the next generation of tech talent to ensure the UK plays a leading role in discovering and developing the latest innovations.  

This sentiment is echoed by business leaders, with our latest ‘Generative AI in the Enterprise’ report revealing that a significant number of businesses are increasing adoption and investment in generative AI. 

Amid unprecedented adoption, business leaders must prepare their workforce for the advent of such technologies in the workplace. This requires greater emphasis on continuous learning and development (L&D), offering ongoing opportunities for employees to develop new skills that are required for the effective and safe use of such technologies. Looking ahead to 2024, what should business leaders do to get started?  

The current state of play  

Understandably, business leaders are pushing ahead with generative AI investments, given its potential to drive growth, optimise operations and deliver exceptional customer experiences. In fact, more than two in five (44%) IT professionals confirmed that their company plans to spend between £25,001–£50,000 on these solutions in the next 12 months alone. 

Yet, we cannot ignore that almost all (93%) IT pros are concerned with their C-suite’s ambitions for the use of generative AI tools, which is due to fears that workplace policy and training opportunities are failing to keep pace.  

According to IT teams, staff outside of their department have been provided limited (32%) or no training opportunities at all (36%) about how generative AI will impact the workplace. As a result, more than a quarter (27%) of IT professionals identified the lack of training for employees as one of their biggest concerns around AI adoption, which is on par with their fears of more advanced cybersecurity threats posed by such technologies.  

This year, increased L&D opportunities will be pivotal in bridging gaps in knowledge – ensuring companies can continue to invest in AI tools but with greater assurance that deployments will be ethical and safe.  

Future-proofing your workforce with a continuous learning culture  

Fortunately, in today’s digital landscape, staff are keen to invest time in their development and take on new opportunities that provide growth opportunities.  

Within IT departments, the majority (82%) of staff want more AI-related L&D opportunities to help advance their current roles. They feel so passionately about it that more than two in five (43%) IT employees have sought external training opportunities over the last twelve months, and a similar amount (61%) are considering moving companies over the next twelve months if their employer fails to provide upskilling opportunities around generative AI. 

These findings highlight that if employers want to recruit and retain the best talent in 2024, they need to play a vital role in creating a culture of continuous learning – empowering staff to take on new challenges, seek out opportunities for growth and share their knowledge with others.  

To help employees prioritise learning around day-to-day responsibilities, companies should consider ‘in the flow of work’ learning opportunities. This concept was coined by Josh Bersin to describe a paradigm in which employees learn something new, quickly apply it and return to their work in progress. While traditional learning approaches such as attending a seminar or conference are effective, many employees simply don’t have the time to devote to them or they prefer to learn at a time that suits them best.  

Instead, ‘in the flow of work’ learning provides employees with the tools needed to quickly find contextually relevant answers to their questions at a time that suits their schedule. Companies can offer more flexible learning opportunities via a trusted L&D partner, who will tailor materials to an individual employee’s unique learning style and objectives and also offer structured learning to upskill. For example, badges are becoming an increasingly popular method for verifying an individual’s knowledge and skills. Because skills training and upskilling opportunities have risen in popularity as benefits that candidates seek, employers can attract and retain key talent by offering ongoing learning opportunities, including the ability to acquire badges.

Looking ahead  

In 2024, successful AI deployments will require more than just investment in cutting-edge solutions. Business leaders should also invest in developing a culture of continuous learning, one that equips employees with the skills and mindset needed to leverage generative AI technologies effectively. 

Comprehensive, more flexible learning opportunities that are accompanied by thorough workplace policies will be essential for innovative enterprise use cases to flourish. At the same time, this will go a long way in enhancing recruitment and retention strategies in the face of a widening technical skills gap. Only with a highly skilled workforce will the UK truly live up to its aspirations of becoming a global leader in AI. 

By Fleur Sexton

Fleur Sexton, Deputy Lieutenant West Midlands and CEO of dynamic training provider, PET-Xi, with a reputation for success with the hardest to reach,

discusses using AI to support excluded pupils in alternative provision (AP)

Exclusion from school is often life-changing for the majority of vulnerable and disadvantaged young people who enter alternative provision (AP). Many face a bleak future, with just 4% of excluded pupils achieving a pass in English and maths GCSEs, and 50% becoming ‘not in  education, employment or training’ (NEET) post-16.

Often labelled ‘the pipeline to prison’, statistics gathered from prison inmates are undeniably convincing: 42% of prisoners were expelled or permanently excluded from school; 59% truanted; 47% of those entering prison have no school qualifications. With a prison service already in crisis, providing children with the ‘right support, right place, right time’, is not just an ethical response, it makes sound financial sense. Let’s invest in education, rather than incarceration.

‘Persistent disruptive behaviour’ – the most commonly cited reason for temporary or permanent exclusion from mainstream education – often results from unmet or undiagnosed special educational needs (SEN) or social, emotional and mental health (SEMH) needs. These pupils find themselves unable to cope in a mainstream environment, which impacts their mental health and personal wellbeing, and their abilities to engage in a positive way with the curriculum and the challenges of school routine. A multitude of factors all adding to their feelings of frustration and failure.

Between 2021/22 and 2022/23, councils across the country recorded a 61% rise in school exclusions, with overall exclusion figures rising by 50% compared to 2018/19. The latest statistics from the Department for  Education (DfE), show pupils with autism in England are nearly three times as likely to be suspended than their neurotypical peers. With 82% of young people in state-funded alternative provision (AP) with identified special educational needs (SEN) and social emotional and mental health (SEMH) needs, for many it is their last chance of gaining an education that is every child’s right.

The Department for Education’s (DfE) SEND and AP Improvement Plan (March 2023).reported, ‘82% of children and young people in state-place funded alternative provision have identified special educational needs (SEN) 2, and it (AP) is increasingly being used to supplement local SEND systems…’

Some pupils on waiting lists for AP placements have access to online lessons or tutors, others are simply at home, and not receiving an education. In oversubscribed AP settings, class sizes have had to be increased to accommodate demand, raising the pupil:teacher ratio, and decreasing the levels of support individuals receive. Other unregulated settings provide questionable educational advantage to attendees.

AI can help redress the balance and help provide effective AP. The first challenge for teachers in AP is to engage these young people back into learning. If the content of the curriculum used holds no relevance for a child already struggling to learn, the task becomes even more difficult. As adults we rarely engage with subjects that do not hold our interest – but often expect children to do so.

Using context that pupils recognise and relate to – making learning integral to the real world and more specifically, to their reality, provides a way in. A persuasive essay about school uniforms, may fire the debate for a successful learner, but it is probably not going to be a hot topic for a child struggling with a chaotic or dysfunctional home life. If that child is dealing with high levels of adversity – being a carer for a relative, keeping the household going, dealing with pressure to join local gangs, being coerced into couriering drugs and weapons around the neighbourhood – school uniform does not hold sway. It has little connection to their life.  

Asking the group about the subjects they feel strongly about, or responding to local news stories from their neighbourhoods, and using these to create tasks, will provide a more enticing hook to pique their interest. After all, in many situations, the subject of a task is  just the ‘hanger’ for the skills they need to learn – in this case, the elements of creating a persuasive piece, communicating perspectives and points of view.

Using AI, teachers have the capacity to provide this individualised content and personalised instruction and feedback, supporting learners by addressing their needs and ‘scaffolding’ their learning through adaptive teaching.

If the learner is having difficulty grasping a concept – especially an abstract one – AI can quickly produce several relevant analogies to help illustrate and explain. It can also be used to develop interactive learning modules, so the learner has more control and ownership over their learning. When engaged with their learning, pupils begin to build skills, increasing their confidence and commitment.

Identifying and discussing these skills and attitudes towards learning, with the pupil reflecting on how they learn and the ways they learn best, also gives them more agency and autonomy, thinking metacognitively.

Gaps in learning are often the cause of confusion, misunderstandings and misconceptions. If a child has been absent from school they may miss crucial concepts that form the building blocks to more complex ideas later in their school career. Without providing the foundations by filling in these gaps and unravelling the misconceptions, new learning may literally be impossible for them to understand, increasing frustration and feelings of failure. AI can help identify those gaps, scaffold learning and build understanding.

AI is by no means a replacement for teachers or teaching assistants, it is purely additional support. Coupled with approaches that promote engagement with learning, AI can enable these disadvantaged young people to access an education previously denied them.

According to the DfE, ‘All children are entitled to receive a world-class education that allows them to reach their potential and live a fulfilled life, regardless of their background.’ AI can help support the most disadvantaged young people towards gaining the education they deserve, and creating a pathway towards educational and social equity.