Google DeepMind CEO Demis Hassabis says AI will create 'new valuable jobs': Here's what to expect

Time of India

4 days ago

Google DeepMind cofounder and CEO Demis Hassabis
As artificial intelligence reshapes the global economy with unprecedented speed, the world stands at the edge of a profound occupational revolution. Just as the steam engine redefined the 19th-century workforce and the internet redrew 21st-century careers, AI is poised to generate an entirely new class of professions, ones that today remain largely unimaginable but imminently necessary.
It's against this backdrop that Demis Hassabis, CEO of Google DeepMind and Nobel laureate, issued a resounding message to the next generation at SXSW London on Monday: STEM disciplines are still indispensable, even in an age increasingly dominated by artificial intelligence.
'It's still important to understand fundamentals' in mathematics, physics, and computer science, Hassabis said, underlining that these subjects form the cognitive scaffolding of the very AI systems now disrupting the job market.
While cautioning against discarding foundational knowledge in favour of automation, Hassabis painted an optimistic picture of a future brimming with 'very valuable new jobs,' roles that reward technical fluency, adaptability, and creative engagement with AI systems. He likened the impact of AI to the Industrial Revolution, not for its displacement, but for its transformative opportunity.
The rise of roles yet unwritten
The AI revolution won't just optimize old jobs; it will forge entirely new professions that today reside only in theoretical outlines. Below are some of the anticipated career domains expected to crystallize over the next 5–10 years:
AI feedback optimizer
An AI Feedback Optimizer is a future-facing professional responsible for fine-tuning AI systems based on real-time human feedback to improve their alignment, relevance, and responsiveness.
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As AI becomes more integrated into everyday applications—customer service bots, educational platforms, therapeutic assistants, and creative tools—this role will bridge the gap between machine output and human expectation.
Core competencies for an AI Feedback Optimizer include expertise in reinforcement learning, human-computer interaction (HCI), natural language processing (NLP), and behavioral psychology.
Strong analytical skills and a deep understanding of user experience are also essential. Relevant degrees include Computer Science, Cognitive Science, Human-Centered Design, or Artificial Intelligence.
Synthetic Data Ethicist
A Synthetic Data Ethicist is a future-focused professional responsible for ensuring that AI systems trained on artificially generated datasets are fair, unbiased, and ethically sound.
As reliance on synthetic data grows, particularly in sensitive sectors like healthcare, finance, and facial recognition, this role becomes crucial in auditing data for hidden biases, ensuring compliance with privacy laws, and evaluating the societal impact of simulated training environments.
The Synthetic Data Ethicist works at the intersection of technology, ethics, and law to prevent harm from skewed or manipulated datasets and to promote transparency in AI development.
Core competencies include data privacy principles, algorithmic fairness, synthetic data generation techniques, and ethical risk modelling. They must also be adept at interdisciplinary collaboration, especially with policymakers, data scientists, and legal teams. Degrees that provide a strong grounding for this role include Data Science, Computer Science with a specialization in AI Ethics, Law (particularly technology and privacy law), or interdisciplinary programmes in Ethics and Emerging Technologies.
As AI adoption accelerates, demand for such ethicists is expected to rise in government agencies, regulatory bodies, research institutions, and any AI-driven enterprise aiming to build responsible systems.
AI Workflow Designer
An AI Workflow Designer is a specialist who architects seamless interactions between human workers and AI systems within complex organizational processes. As businesses integrate AI into everything from logistics and marketing to customer support and research, this role ensures that automation enhances, rather than disrupts, productivity and user experience.
The AI Workflow Designer maps tasks, identifies automation opportunities, and builds adaptive workflows where AI tools support human decision-making while preserving transparency and accountability.
This role demands a deep understanding of systems thinking, process optimization, and cross-functional collaboration. Core competencies include knowledge of AI integration platforms, UX/UI principles, business process modelling, and change management.
Proficiency in tools like BPMN (Business Process Model and Notation), APIs, and machine learning pipelines is often essential.
Relevant degrees include Industrial Engineering, Systems Design, Human-Computer Interaction, or Computer Science with a focus on enterprise AI systems. With industries racing toward AI augmentation, the AI Workflow Designer will become pivotal in ensuring that technological transformation is not only efficient but also human-centric.
Algorithmic Bias Auditor
An Algorithmic Bias Auditor is a critical watchdog in the AI development pipeline, tasked with identifying, measuring, and mitigating biases embedded in algorithms that impact real-world decisions, from hiring and lending to policing and healthcare. As AI systems increasingly influence high-stakes outcomes, this role ensures that their outputs are fair, transparent, and aligned with ethical and legal standards.
The auditor conducts audits on training data, model architecture, and decision outputs, using statistical tools and fairness metrics to uncover hidden prejudices and systemic discrimination.
Core competencies include deep knowledge of algorithmic fairness frameworks, statistical bias detection techniques, legal literacy in anti-discrimination laws, and experience with machine learning auditing tools.
Strong communication skills are also essential to translate technical findings into actionable insights for diverse stakeholders. Degrees that support this role include Data Science, Applied Ethics, Law with a focus on technology policy, or Computer Science with a specialization in AI fairness. As AI accountability becomes a global priority, Algorithmic Bias Auditors will be vital to building public trust and regulatory compliance in both private and public sector AI deployments.
Prompt Architecture
A Prompt Systems Architect is a future-ready specialist who designs, tests, and refines sophisticated prompt structures that guide advanced AI models, such as large language models and multimodal systems, to produce accurate, context-aware, and goal-specific outputs.
As generative AI becomes central to industries like law, education, healthcare, and enterprise automation, this role ensures that prompts are not only effective but also scalable, reusable, and aligned with organizational needs. The architect creates layered prompt frameworks, integrates domain-specific context, and optimizes input-output loops to enhance performance, reliability, and interpretability.
Core competencies include expertise in natural language processing (NLP), prompt engineering, domain modelling, and AI system behaviour.
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