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Scientists may also have succeeded in using generative AI to designantibodies that bind to a human protein linked tocancer.36AI is used in the fight against the most serious and harmful crimesThe Child Images AbuseDatabase37uses the powerful data processingcapabilities of AI to identify victims and perpetrators of child sexual abuse.Thequick and effective identification of victims and perpetrators in digital abuse imagesMia mammography intelligent assessment,NHS England,2021.Robotics and Autonomous Systems for Net Zero Agriculture,Pearson et al.,2022.Artificial intelligence,big data and machine learning approaches to precision medicine and drug discovery,Current DrugTargets,2021.Unlocking de novo antibody design with generative artificial intelligence,Shanehsazzadeh et al.,2023.Pioneering new tools to be rolled out in fight against child abusers,Home Office,2019.A pro-innovation approach to AI regulationallows for real world action to remove victims from harm and ensure their abusersare held to account.The use of AI increases the scale and speed of analysis whileprotecting staff welfare by reducing their exposure to distressing content.AI increases cyber security capabilitiesCompanies providing cyber security services are increasingly using AI to analyselarge amounts of data about malware and respond to vulnerabilities in networksecurity at faster-than-humanspeeds.38As the complexity of the cyber threatlandscape evolves,the pattern-recognition and recursive learning capabilities of AIare likely to play an increasingly significant role in proactive cyber defence againstmalicious actors.1.2 Managing AI risks

Terminology used in thispaper:50AI or AI system or AI technologies:products and services that are ‘adaptable’ and‘autonomous’ in the sense outlined in our definition in section 3.2.1.AI supplier:any organisation or individual who plays a role in the research,development,training,implementation,deployment,maintenance,provision or sale of AI systems.AI user:any individual or organisation that uses an AI product.AI life cycle:all events and processes that relate to an AI system’s lifespan,frominception to decommissioning,including its design,research,training,development,deployment,integration,operation,maintenance,sale,use and governance.AI ecosystem:the complex network of actors and processes that enable the use andsupply of AI throughout the AI life cycle(including supply chains,markets,and governancemechanisms).Foundation model:a type of AI model that is trained on a vast quantity of data and isadaptable for use on a wide range of tasks.Foundation models can be used as a base forbuilding more specific AI models.Foundation models are discussed in more detail insection 3.3.3below.51Impacted third party:an individual or company that is impacted by the outcomes of theAI systems that they do not use or supply themselves.‘Is ChatGPT a cybersecurity threat?’ TechCrunch,2023.OPWNAI:Cybercriminals starting to use ChatGPT,Check Point Research,2023.These are not intended to be legal definitions for the purposes of the framework.The value chain of general-purpose AI,Ada Lovelace Institute,2023.A pro-innovation approach to AI regulationPart Two:The current regulatoryenvironment2.1 Navigating the current landscape