制药行业AI赋能企业经营的工具有哪些

The audience for an explanation of AI’s outcomes will often be a regulator,who may require a higher standard of explainability depending on the risks represented by an application.The MHRA’s Project Glass Box work is addressing the challenge of setting medical device requirements that take into account adequate consideration of human interpretability and its consequences for the safety and effectiveness for AI used in medical devices.107105 Responsible Innovation in Self-Driving Vehicles,CDEI,2022.106 Explaining decisions made with AI,ICO and the Alan Turing Institute,2021.107 Software and AI as a Medical Device Change Programme–Roadmap,MHRA,2022.34A pro-innovation approach to AI regulationCase Study 3.5:What the principles mean for businesses in practiceA fictional company,“Good AI Recruitment Limited”,provides recruitment services that use a range of AI systems to accelerate the recruitment process,including a service that automatically shortlists candidates based on application forms.While potentially useful,such systems may discriminate against certain groups that have historically not been selected for certain positions.After the implementation of the UK’s new AI regulatory framework,the Equality and Human Rights Commission(EHRC)and the Information Commissioner Office(ICO)will be supported and encouraged to work with the Employment Agency Standards Inspectorate(EASI)and other regulators and organisations in the employment sector to issue joint guidance.The joint guidance could address the cross-cutting principles relating to fairness,appropriate transparency and explainability,and contestability and redress in the context of the use of AI systems in recruitment or employment.Such joint guidance could,for example,make things clearer and easier for Good AI Recruitment Limited by:

1.27.While AI is currently regulated through existing legal frameworks like financial services regulation,60 some AI risks arise across,or in the gaps between,existing regulatory remits.Industry told us that conflicting or uncoordinated requirements from regulators create unnecessary burdens and that regulatory gaps may leave risks unmitigated,harming public trust and slowing AI adoption.2.28.Industry has warned us that regulatory incoherence could stifle innovation and competition by causing a disproportionate amount of smaller businesses to leave the market.If regulators are not proportionate and aligned in their regulation of AI,businesses may have to spend excessive time and money complying with complex rules instead of creating new technologies.Small businesses and start-ups often do not have the resources to do both.61 With the vast majority of digital technology businesses employing under 50 people,62 it is important to ensure that regulatory burdens do not fall disproportionately on smaller companies,which play an essential role in the AI innovation ecosystem and act as engines for economic growth and job creation.633.29.Regulatory coordination will support businesses to invest confidently in AI innovation and build public trust by ensuring real risks are effectively addressed.While some regulators already work together to ensure regulatory coherence for AI through formal networks like the AI and digital regulations service in the health sector64 and the Digital Regulation Cooperation Forum(DRCF),other regulators have limited capacity and access to AI expertise.This creates the risk of inconsistent enforcement across regulators.There is also a risk that some regulators could begin to dominate and interpret the scope of their remit or role more broadly than may have been intended in order to fill perceived gaps in a way that increases incoherence and uncertainty.Industry asked us to support further system-wide coordination to clarify who is59 Consumer Rights Act 2015;Consumer Protection from Unfair Trading Regulations,HM Government,2008.

1.19.AI is already delivering major advances and efficiencies in many areas.AI quietly automates aspects of our everyday activities,from systems that monitor traffic to make our commutes smoother,17 to those that detect fraud in our bank accounts.18 AI has revolutionised large-scale safety-critical practices in industry,like controlling the process of nuclear fusion.19 And it has also been used to accelerate scientific advancements,such as the discovery of new medicine20 or the technologies we need to tackle climate change.212.20.But this is just the beginning.AI can be used in a huge variety of settings and has the extraordinary potential to transform our society and economy.22 It could have as much impact as electricity or the internet,and has been identified as one of five critical technologies in the UK Science and Technology Framework.23 As AI becomes more powerful,and as innovators explore new ways to use it,we will see more applications of AI emerge.As a result,AI has a huge potential to drive growth24 and create jobs.25 It will support people to carry out their existing jobs,by helping to improve workforce efficiency and workplace safety.26 To remain world leaders in AI,attract global talent and create high-skilled jobs in the UK,we must create a regulatory environment where such innovation can thrive.3.21.Technological advances like large language models(LLMs)are an indication of the transformative developments yet to come.27 LLMs provide substantial opportunities to transform the economy and society.For example,LLMs can automate the process of writing code and17 Transport apps like Google Maps,and CityMapper,use AI.18 Artificial Intelligence in Banking Industry:A Review on Fraud Detection,Credit Management,and Document Processing,ResearchBerg Review of Science and Technology,2018.19 Accelerating fusion science through learned plasma control,Deepmind,2022;Magnetic control of tokamak plasmas through deep reinforcement learning,Degrave et al.,2022.