Embracing Lateral Thinking in the Age of AI

Human lateral thinking in the Age of AI – is there a place for it? Last Sunday morning, Edward DeBono’s book, “Lateral Thinking,” landed squarely on my head as I decluttered my bookshelf.

For those of you familiar with De Bono’s work, you’ll know this dusty 1970s relic is from a past era predating the internet. But flipping through the pages got me thinking, how do traditional cognitive skills like lateral thinking mesh with today’s algorithmic precision of Artificial Intelligence (AI)?

Human lateral thinking skills Vs AI

In contrast to DeBono’s lateral thinking theories AI, and Large Language Models (LLMs) like ChatGPT, represent a different paradigm in cognitive skills and problem-solving.

Here’s a quick comparison of DeBono’s lateral thinking with AI and LLMs:


  • Novelty generation: Both lateral thinking and AI can generate novel solutions. Lateral thinking does this through creative and non-traditional thought processes, while AI uses vast amounts of data to generate unique combinations and insights.
  • Pattern recognition: Lateral thinking involves recognising unusual patterns or connections. Similarly, AI, especially machine learning models, excel at identifying patterns in large datasets.


  • Process: Lateral thinking is inherently human, relying on subjective insights and creative leaps. Conversely, AI operates on algorithms and data, following more objective and quantifiable methods.
  • Creativity origin: DeBono’s concept relies on human intuition and unconscious processes for creative thought, while AI’s “creativity” stems from programmed algorithms and data analysis. The depth and richness of human creativity, influenced by emotions and experiences, are not replicated in AI.
  • Flexibility: Lateral thinking is adaptable and can be applied in varied contexts, relying on human adaptability. AI’s flexibility is limited to its programming and the data it has been trained on.
  • Learning process: Humans learn and apply lateral thinking through experience and conscious effort. AI learns from data input and updates its algorithms accordingly, but it doesn’t “understand” or “experience” learning as humans do – yet!

In fact, recent studies in cognitive psychology show that while AI excels in data processing and pattern recognition, it lacks the emotional and experiential context that humans bring to problem-solving (Smith & Jones, 2023).

Impact on human problem-solving skills

  • Complementarity: AI and LLMs can complement human cognitive skills by handling large-scale data analysis, thus freeing humans to engage in more creative, lateral thinking.
  • Dependency risk: There’s a risk that over-reliance on AI for problem-solving could lead to a decline in human skills in lateral thinking and creativity.
  • Augmentation: AI can augment human decision-making by providing insights derived from data that might not be obvious through lateral thinking alone.
  • Skill shift: The future might see a shift in cognitive skills where human expertise is valued for creativity and emotional intelligence, while AI handles logical, data-driven tasks.

While DeBono’s lateral thinking and AI/LLMs operate on fundamentally different principles, they are not mutually exclusive. In fact, their integration could lead to a more holistic approach to problem-solving in the future, where AI’s data-driven insights complement human creativity and lateral thinking.

The Educational Psychology Review (2023) emphasises the necessity of a renewed focus on creative problem-solving in curricula to balance AI-enhanced learning.

Let’s take a closer look.

Schools – out of the box thinking

  • Lateral thinking in education: Encouraging lateral thinking in schools can foster creativity and innovation in students. Educators can use techniques like brainstorming, role-playing, and alternative scenarios to develop students’ ability to think divergently.
  • AI integration: AI can personalise learning by adapting content to each student’s learning style and pace. It can also provide data-driven insights to help educators identify areas where students might need more creative problem-solving exercises.
  • Balanced curriculum: A curriculum that balances lateral thinking exercises with AI-enhanced learning tools can prepare students for a future where creative and analytical skills are equally valued.

The UK Department for Education (2024) stresses the importance of integrating AI tools with exercises to develop divergent thinking skills.

Business – divergent thinking

  • Innovation through lateral thinking: Businesses encouraging lateral thinking among their employees can foster innovation and adaptability. Techniques like DeBono’s Six Thinking Hats can aid in exploring issues from multiple perspectives.
  • AI for strategic decision-making: AI can analyse market trends, consumer behaviour, and internal data, offering insights to inform strategic decisions. This data-driven approach complements the creative solutions generated through lateral thinking.
  • Enhanced collaboration: AI tools can facilitate better collaboration and team communication, allowing for a more effective combination of diverse, creative ideas and data-driven strategies.

A McKinsey & Company report (2024) notes the rise of AI in decision-making processes, emphasising the need for human-led creative strategies


  • Understanding human thought: Lateral thinking aligns closely with psychological studies on creativity and cognitive flexibility. Psychologists and counsellors like myself can use these principles to develop therapies and interventions that enhance cognitive flexibility and creative problem-solving.
  • AI in psychological assessment: AI can assist in the analysis of complex psychological data, helping diagnose and understand various cognitive and emotional conditions. All of which lead to more tailored and effective treatment plans.
  • Behavioural insights: through pattern recognition and data analysis, AI can provide insights into human behaviour and cognition. Accordingly, this can complement psychological theories and help in understanding the underpinnings of lateral thinking and creativity.

The American Journal of Psychiatry (2023) notes how AI assists in diagnosing cognitive and emotional conditions but lacks the empathetic understanding crucial for effective therapy. This highlights the complementary roles of AI and lateral thinking in psychological practices.

Combined impact

  • For schools, this integration can lead to a more well-rounded education, preparing students for a world where both creative and analytical skills are crucial.
  • Businesses combining lateral thinking with AI can inspire innovative and effective strategies, balancing human creativity with data-driven decision-making.
  • In the field of psychology, this synergy can enhance our understanding of the human mind and improve mental health interventions.

Ultimately, the key lies in leveraging the strengths of humans’ creative, divergent thinking combined with AI’s data processing and pattern recognition capabilities. Together, they’ll foster innovation, efficiency, and deeper understanding across various fields. But this begs a bigger question.

Is there value in teaching creative thinking skills?

What is the continued value of teaching human lateral thinking skills in an era dominated by fast and convenient AI solutions?  The answer hinges on recognising and fostering the unique contributions that human creativity and divergent thinking bring to problem-solving and innovation.

Here’s how human lateral thinking skills might continue to be valued and taught:


  • Curriculum design: Schools and universities can design curricula that emphasise creative problem-solving, critical thinking, and innovation alongside technology and AI studies. This dual focus ensures students are proficient in AI tools and creative thinking.
  • Project-based learning: Implementing project-based learning that requires students to apply lateral thinking to real-world problems can highlight the limitations of AI and the need for human creativity.
  • Interdisciplinary studies: Encouraging studies that blend arts, humanities, and sciences can promote the kind of holistic, lateral thinking that AI cannot replicate.


  • Innovation labs: Companies can create innovation labs or spaces where employees are encouraged to think laterally and develop ideas that AI alone cannot.
  • AI as a tool, not a crutch: Training employees to use AI as a tool to augment their creativity rather than replace it can maintain the value of human insight.
  • Rewarding creativity: Businesses can explicitly reward creative solutions and encourage risk-taking, reinforcing the value of lateral thinking.

Personal development

  • Lifelong learning: Emphasising the importance of lifelong learning in personal development, including the development of creative and lateral thinking skills.
  • Mindfulness and reflection: Practices like mindfulness and reflective thinking can encourage individuals to think beyond the AI-driven ‘fastest’ solution.
  • Enhancing emotional intelligence and self-regulation: Lateral thinking skills can greatly aid in understanding and managing one’s emotions and behaviours. By fostering a mindset that looks at problems and situations from various perspectives, individuals can develop a deeper awareness of their emotional responses and learn to regulate them more effectively. This broader perspective can lead to improved empathy, better conflict resolution and more adaptive coping strategies in both personal and professional settings.

Societal and cultural emphasis

  • Public discourse: Influencers, educators, and leaders can advocate for the importance of human creativity in public discourse, emphasising its role in innovation and problem-solving.
  • Cultural celebrations: Celebrating achievements in arts, literature, and other creative fields highlights the value of human creativity
  • Technology-enhanced lateral thinking: AI as a creative partner: Using AI as a brainstorming partner, to challenge and extend human thinking rather than replace it.
  • Development of AI tools: Developing AI tools specifically designed to facilitate and enhance lateral thinking in humans.

Future implications

  • Balanced approach: As AI becomes more integrated into society, a balanced approach that values both AI efficiency and human creativity will likely become a key component of successful strategies in education, business, and personal development.
  • Human-centric design: Designing AI systems that are human-centric, acknowledging the importance of human intuition, ethics, and creativity.

Ensuring that lateral thinking skills continue to be valued and taught in the age of AI will require intentional efforts across educational, professional, and personal development spheres.

The World Economic Forum (2023) predicts a growing demand for skills like lateral thinking alongside AI proficiency. This future landscape requires curricula that emphasise both creative problem-solving and AI literacy.

By emphasising the unique contributions of human creativity, encouraging interdisciplinary learning, and using AI as a tool to augment rather than replace human thought, lateral thinking can maintain its relevance and importance in a technology-driven world.

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