Artificial Intelligence (AI) In Healthcare And Research

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Artificial intelligence (AI) in healthcare and researchOVERVIEW AI is being used or trialled for a range ofhealthcare and research purposes, includingdetection of disease, management of chronicconditions, delivery of health services, anddrug discovery. AI has the potential to help addressimportant health challenges, but might belimited by the quality of available health data,and by the inability of AI to display somehuman characteristics. The use of AI raises ethical issues, including:the potential for AI to make erroneousdecisions; the question of who is responsiblewhen AI is used to support decision-making;difficulties in validating the outputs of AIsystems; inherent biases in the data usedto train AI systems; ensuring the protectionof potentially sensitive data; securing publictrust in the development and use of AItechnologies; effects on people’s sense ofdignity and social isolation in care situations;effects on the roles and skill-requirements ofhealthcare professionals; and the potentialfor AI to be used for malicious purposes. A key challenge will be ensuring that AIis developed and used in a way that istransparent and compatible with the publicinterest, whilst stimulating and drivinginnovation in the sector.WHAT IS AI?There is no universally agreed definition of AI. Theterm broadly refers to computing technologiesthat resemble processes associated withhuman intelligence, such as reasoning, learningand adaptation, sensory understanding, andinteraction.1 Currently, most applications of AIare narrow, in that they are only able to carry outspecific tasks or solve pre-defined problems.2

AI works in a range of ways, drawing onprinciples and tools, including from maths,logic, and biology. An important feature ofcontemporary AI technologies is that they areincreasingly able to make sense of varied andunstructured kinds of data, such as naturallanguage text and images. Machine-learning hasbeen the most successful type of AI in recentyears, and is the underlying approach of manyof the applications currently in use.3 Rather thanfollowing pre-programmed instructions, machinelearning allows systems to discover patterns andderive its own rules when it is presented withdata and new experiences.4RECENT INTEREST IN AIAI is not new, but there have been rapidadvances in the field in recent years. This has inpart been enabled by developments in computingpower and the huge volumes of digital data thatare now generated.5 A wide range of applicationsof AI are now being explored with considerablepublic and private investment and interest. TheUK Government announced its ambition to makethe UK a world leader in AI and data technologiesin its 2017 Industrial Strategy. In April 2018, a 1bn AI sector deal between UK Governmentand industry was announced, including 300million towards AI research.6AI is lauded as having the potential to helpaddress important health challenges, such asmeeting the care needs of an ageing population.Major technology companies - includingGoogle, Microsoft, and IBM - are investing in thedevelopment of AI for healthcare and research.The number of AI start-up companies has alsobeen steadily increasing.7 There are several UKbased companies, some of which have beenset up in collaboration with UK universitiesand hospitals. Partnerships have been formedbetween NHS providers and AI developerssuch as IBM, DeepMind, Babylon Health, andUltromics.Such partnerships have attracted controversy,and wider concerns about AI have been the focusof several inquiries and initiatives within industry,and medical and policy communities (see Box 1).BOX 1. EXAMPLES OF INQUIRIES AND INITIATIVES ON AI UK Government Centre for Data Ethicsand Innovation – announced in January2018 to advise on safe, ethical, andinnovative uses of data-driven technologies.8 Ada Lovelace Institute – the NuffieldFoundation announced it will set up theInstitute by the end of 2018 to examineethical and social issues arising from the useof data, algorithms, and AI, ensuring they areharnessed for social well-being.9 Partnership on AI – a platform fordiscussion and engagement around AIfounded by Amazon, Apple, DeepMind,Facebook, Google, IBM, and Microsoft.10 IEEE – launched a Global Initiative on Ethicsof Autonomous and Intelligent Systems in2016.11 United Nations Interregional Crime andJustice Research Institute – set up aprogramme on Artificial Intelligence andRobotics in 2015.12 Asilomar AI Principles – developed in 2017by the Future of Life Institute (US) to guide AIresearch and application, and signed by over3,800 researchers and others working in AIand robotics around the world.13 Reports on AI have been published bythe House of Lords Select Committeeon Artificial Intelligence,5 the RoyalSociety,3 Reform,14 Future Advocacy andWellcome,15 Nesta,16 and the EuropeanGroup on Ethics in Science and NewTechnologies.17 A further report is expectedfrom the House of Commons Science andTechnology Select Committee.18Nuffield Council on Bioethics 2

APPLICATIONS OF AI IN HEALTHCARE AND RESEARCHHEALTHCARE ORGANISATIONPossible uses of AI in clinical care include:AI has the potential to be used in planning andresource allocation in health and social careservices. For example, the IBM Watson CareManager system is being piloted by HarrowCouncil with the aim of improving cost efficiency.It matches individuals with a care provider thatmeets their needs, within their allocated carebudget. It also designs individual care plans, andclaims to offer insights for more effective use ofcare management resources.19 Medical imaging – medical scans havebeen systematically collected and stored forsome time and are readily available to trainAI systems.27 AI could reduce the cost andtime involved in analysing scans, potentiallyallowing more scans to be taken to better targettreatment.5 AI has shown promising resultsin detecting conditions such as pneumonia,breast and skin cancers, and eye diseases.28 Echocardiography – the Ultromics system,trialled at John Radcliffe Hospital in Oxford,uses AI to analyse echocardiography scansthat detect patterns of heartbeats and diagnosecoronary heart disease.29 Screening for neurological conditions – AItools are being developed that analyse speechpatterns to predict psychotic episodes andidentify and monitor symptoms of neurologicalconditions such as Parkinson’s disease.30 Surgery – robotic tools controlled by AI havebeen used in research to carry out specifictasks in keyhole surgery, such as tying knots toclose wounds.31AI is also being used with the aim of improvingpatient experience. Alder Hey Children’s Hospitalin Liverpool is working with IBM Watson to createa ‘cognitive hospital’, which will include an app tofacilitate interactions with patients. The app aimsto identify patient anxieties before a visit, provideinformation on demand, and equip clinicians withinformation to help them to deliver appropriatetreatments.20MEDICAL RESEARCHAI can be used to analyse and identify patternsin large and complex datasets faster and moreprecisely than has previously been possible.21It can also be used to search the scientificliterature for relevant studies, and to combinedifferent kinds of data; for example, to aid drugdiscovery.22 The Institute of Cancer Research’scanSAR database combines genetic and clinicaldata from patients with information from scientificresearch, and uses AI to make predictions aboutnew targets for cancer drugs.23 Researchershave developed an AI ‘robot scientist’ calledEve which is designed to make the process ofdrug discovery faster and more economical.24AI systems used in healthcare could also bevaluable for medical research by helping to matchsuitable patients to clinical studies.25CLINICAL CAREAI has the potential to aid the diagnosis ofdisease and is currently being trialled for thispurpose in some UK hospitals. Using AI toanalyse clinical data, research publications, andprofessional guidelines could also help to informdecisions about treatment.26PATIENT AND CONSUMER-FACINGAPPLICATIONSSeveral apps that use AI to offer personalisedhealth assessments and home care advice arecurrently on the market. The app Ada HealthCompanion uses AI to operate a chat-bot, whichcombines information about symptoms fromthe user with other information to offer possiblediagnoses.32 GP at Hand, a similar app developedby Babylon Health, is currently being trialled by agroup of NHS surgeries in London.33Information tools or chat-bots driven by AI arebeing used to help with the management ofchronic medical conditions. For example, theArthritis Virtual Assistant developed by IBMfor Arthritis Research UK is learning throughinteractions with patients to provide personalisedinformation and advice concerning medicines,diet, and exercise.34 Government-funded andcommercial initiatives are exploring ways inwhich AI could be used to power robotic systemsand apps to support people living at homewith conditions such as early stage dementia,Bioethics briefing note: Artificial intelligence (AI) in healthcare and research 3

potentially reducing demands on human careworkers and family carers.35and prevent hospital admissions.37PUBLIC HEALTHAI apps that monitor and support patientadherence to prescribed medication andtreatment have been trialled with promisingresults, for example, in patients withtuberculosis.36 Other tools, such as Sentrian, useAI to analyse information collected by sensorsworn by patients at home. The aim is to detectsigns of deterioration to enable early interventionAI has the potential to be used to aid earlydetection of infectious disease outbreaksand sources of epidemics, such as watercontamination.38 AI has also been used to predictadverse drug reactions, which are estimated tocause up to 6.5 per cent of hospital admissionsin the UK.39LIMITS OF AIAI depends on digital data, so inconsistenciesin the availability and quality of data restrict thepotential of AI. Also, significant computing poweris required for the analysis of large and complexdata sets. While many are enthusiastic aboutthe possible uses of AI in the NHS, others pointto the practical challenges, such as the fact thatmedical records are not consistently digitisedacross the NHS, and the lack of interoperabilityand standardisation in NHS IT systems, digitalrecord keeping, and data labelling.5 There arequestions about the extent to which patients anddoctors are comfortable with digital sharing ofpersonal health data.40Humans have attributes that AI systems mightnot be able to authentically possess, such ascompassion.41 Clinical practice often involvescomplex judgments and abilities that AI currentlyis unable to replicate, such as contexualknowledge and the ability to read social cues.16There is also debate about whether some humanknowledge is tacit and cannot be taught.42Claims that AI will be able to display autonomyhave been questioned on grounds that this isa property essential to being human and bydefinition cannot be held by a machine.17ETHICAL AND SOCIAL ISSUESMany ethical and social issues raised byAI overlap with those raised by data use;automation; the reliance on technologies morebroadly; and issues that arise with the use ofassistive technologies and ‘telehealth’.The performance of symptom checker appsusing AI, has been questioned. For example, ithas been found that recommendations from appsmight be overly cautious, potentially increasingdemand for uneccessary tests and treatments.16RELIABILITY AND SAFETYTRANSPARENCY AND ACCOUNTABILITYReliability and safety are key issues where AI isused to control equipment, deliver treatment,or make decisions in healthcare. AI could makeerrors and, if an error is difficult to detect orhas knock-on effects, this could have seriousimplications.43 For example, in a 2015 clinical trial,an AI app was used to predict which patientswere likely to develop complications followingpneumonia, and therefore should be hospitalised.This app erroneously instructed doctors to sendhome patients with asthma due to its inability totake contextual information into account.44It can be difficult or impossible to determinethe underlying logic that generates the outputsproduced by AI.45 Some AI is proprietary anddeliberately kept secret, but some are simply toocomplex for a human to understand.46 Machinelearning technologies can be particularly opaquebecause of the way they continuously tweak theirown parameters and rules as they learn.47 Thiscreates problems for validating the outputs of AIsystems, and identifying errors or biases in thedata.Nuffield Council on Bioethics 4

The new EU General Data Protection Regulation(GDPR) states that data subjects have the rightnot to be subject to a decision based solelyon automated processing that produces legalor similarly significant effects. It further statesthat information provided to individuals whendata about them are used should include “theexistence of automated decision-making, (.)meaningful information about the logic involved,as well as the significance and the envisagedconsequences of such processing for the datasubject”.48 However, the scope and content ofthese restrictions - for example, whether and howAI can be intelligible - and how they will applyin the UK, remain uncertain and contested.49Related questions include who is accountable fordecisions made by AI and how anyone harmedby the use of AI can seek redress.3DATA BIAS, FAIRNESS, AND EQUITYAlthough AI applications have the potential toreduce human bias and error, they can alsoreflect and reinforce biases in the data used totrain them.50 Concerns have been raised aboutthe potential of AI to lead to discrimination inways that may be hidden or which may not alignwith legally protected characteristics, such asgender, ethnicity, disability, and age.51 The Houseof Lords Select Committee on AI has cautionedthat datasets used to train AI systems are oftenpoorly representative of the wider populationand, as a result, could make unfair decisions thatreflect wider prejudices in society. The Committeealso found that biases can be embedded in thealgorithms themselves, reflecting the beliefsand prejudices of AI developers.52 Severalcommentators have called for increased diversityamong developers to help address this issue.53The benefits of AI in healthcare might not beevenly distributed. AI might work less well wheredata are scarce or more difficult to collect orrender digitally.54 This could affect people withrare medical conditions, or others who areunderrepresented in clinical trials and researchdata, such as Black, Asian, and minority ethnicpopulations.55TRUSTThe collaboration between DeepMind and theRoyal Free Hospital in London led to publicdebate about commercial companies being givenaccess to patient data.56 Commentators havewarned that there could be a public backlashagainst AI if people feel unable to trust that thetechnologies are being developed in the publicinterest.57At a practical level, both patients and healthcareprofessionals will need to be able to trustAI systems if they are to be implementedsuccessfully in healthcare.58 Clinical trials ofIBM’s Watson Oncology, a tool used in cancerdiagnosis, was reportedly halted in someclinics as doctors outside the US did not haveconfidence in its recommendations, and feltthat the model reflected an American-specificapproach to cancer treatment.59EFFECTS ON PATIENTSAI health apps have the potential to empowerpeople to evaluate their own symptoms andcare for themselves when possible. AI systemsthat aim to support people with chronic healthconditions or disabilities could increase people’ssense of dignity, independence, and quality oflife; and enable people who may otherwise havebeen admitted to care institutions to stay at homefor longer.60 However, concerns have been raisedabout a loss of human contact and increasedsocial isolation if AI technologies are used toreplace staff or family time with patients.61AI systems could have a negative impact onindividual autonomy: for example, if they restrictchoices based on calculations about risk orwhat is in the best interests of the user.62 If AIsystems are used to make a diagnosis or devisea treatment plan, but the healthcare professionalis unable to explain how these were arrived at,this could be seen as restricting the patient’sright to make free, informed decisions abouttheir health.63 Applications that aim to imitate ahuman companion or carer raise the possibilitythat the user will be unable to judge whether theyare communicating with a real person or withtechnology. This could be experienced as a formof deception or fraud.64EFFECTS ON HEALTHCARE PROFESSIONALSHealthcare professionals may feel that theirautonomy and authority is threatened if theirexpertise is challenged by AI.65 The ethicalobligations of healthcare professionals towardsindividual patients might be affected by the use ofAI decision support systems, given these mightBioethics briefing note: Artificial intelligence (AI) in healthcare and research 5

be guided by other priorities or interests, such ascost efficiency or wider public health concerns.66As with many new technologies, the introductionof AI is likely to mean the skills and expertiserequired of healthcare professionals will change.In some areas, AI could enable automation oftasks that have previously been carried out byhumans.2 This could free up health professionalsto spend more time engaging directly withpatients. However, there are concerns that theintroduction of AI systems might be used tojustify the employment of less skilled staff.67 Thiscould be problematic if the technology fails andstaff are not able to recognise errors or carry outnecessary tasks without computer guidance. Arelated concern is that AI could make healthcareprofessionals complacent, and less likely tocheck results and challenge errors.68DATA PRIVACY AND SECURITYAI applications in healthcare make use of datathat many would consider to be sensitive andprivate. These are subject to legal controls.69However, other kinds of data that are notobviously about health status, such as socialmedia activity and internet search history, couldbe used to reveal information about the healthstatus of the user and those around them. TheNuffield Council on Bioethics has suggested thatinitiatives using data that raise privacy concernsshould go beyond compliance with the law totake account of people’s expectations about howtheir data will be used.70AI could be used to detect cyber-attacks andprotect healthcare computer systems. However,there is the potential for AI systems to be hackedto gain access to sensitive data, or spammedwith fake or biased data in ways that might noteasily be detectable.71MALICIOUS USE OF AIWhile AI has the potential to be used for good, itcould also be used for malicious purposes. Forexample, there are fears that AI could be used forcovert surveillance or screening. AI technologiesthat analyse motor behaviour, (such as the waysomeone types on a keyboard), and mobilitypatterns detected by tracking smartphones,could reveal information about a person’s healthwithout their knowledge.72 AI could be used tocarry out cyber-attacks at a lower financial costand on a greater scale.73 This has led to callsfor governments, researchers, and engineers toreflect on the dual use nature of AI and preparefor possible malicious uses of AI technologies.73CHALLENGES FOR GOVERNANCEAI has applications in fields that are subject toregulation, such as data protection, research,and healthcare. However, AI is developing in afast-moving and entrepreneurial manner thatmight challenge these established frameworks.A key question is whether AI should be regulatedas a distinct area, or whether different areas ofregulation should be reviewed with the possibleimpact of AI in mind.5Further challenges include the need to ensurethat the way AI is developed and used istransparent, accountable, and compatible withpublic interest, and balanced with the desire tod

Artificial intelligence (AI) in healthcare and research. RECENT INTEREST IN AI AI is not new, but there have been rapid advances in the field in recent years.This has in part been enabled by developments in computing power and the huge volumes of digital data that are now generated.5 A wide range of applications of AI are now being explored with considerable public and private investment and .

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