Man and Machine: Questions of Risk, Trust and Accountability in Today's AI Technology

Artificial Intelligence began as a field probing some of the most fundamental questions of science - the nature of intelligence and the design of intelligent artifacts. But it has grown into a discipline that is deeply entwined with commerce and society. Today's AI technology, such as expert systems and intelligent assistants, pose some difficult questions of risk, trust and accountability. In this paper, we present these concerns, examining them in the context of historical developments that have shaped the nature and direction of AI research. We also suggest the exploration and further development of two paradigms, human intelligence-machine cooperation, and a sociological view of intelligence, which might help address some of these concerns.Comment: Preprin

Where Are My Intelligent Assistant's Mistakes? A Systematic Testing Approach

Intelligent assistants are handling increasingly critical tasks, but until now, end users have had no way to systematically assess where their assistants make mistakes. For some intelligent assistants, this is a serious problem: if the assistant is doing work that is important, such as assisting with qualitative research or monitoring an elderly parent’s safety, the user may pay a high cost for unnoticed mistakes. This paper addresses the problem with WYSIWYT/ML (What You See Is What You Test for Machine Learning), a human/computer partnership that enables end users to systematically test intelligent assistants. Our empirical evaluation shows that WYSIWYT/ML helped end users find assistants’ mistakes significantly more effectively than ad hoc testing. Not only did it allow users to assess an assistant’s work on an average of 117 predictions in only 10 minutes, it also scaled to a much larger data set, assessing an assistant’s work on 623 out of 1,448 predictions using only the users’ original 10 minutes’ testing effort

Supporting general hospital staff to provide dementia sensitive care: A realist evaluation

© 2019 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0).Background: There are an increasing number of interventions to improve hospital care for patients with dementia. Evidence for their impact on staff actions and patient outcomes is, however, limited and context dependent. Objective: To explain the factors that support hospital staff to provide dementia sensitive care and with what outcomes for patients with dementia. Design: A realist evaluation using a two-site case study approach. Setting: Two hospital trusts in the East of England. Site 1 had a ward for patients with dementia that would address their medical and mental health needs. Site 2 used a team of healthcare assistants, who had support from dementia specialist nurses, to work with patients with dementia across the hospital. Participants: Hospital staff who had a responsibility for inpatients with dementia (healthcare assistants, nurses, medical staff, allied healthcare professionals and support staff) (n = 36), patients with dementia (n = 28), and family carers of patients with dementia (n = 2). Methods: A three stage realist evaluation: 1) building the programme theory of what works and when; 2) testing the programme theory through empirical data (80 h non-participant observation, 42 interviews, 28 patient medical notes, 27 neuropsychiatric inventory, and documentary review); 3) synthesis and verification of findings with key stakeholders. Findings: The programme theory comprised six interconnected context-mechanism-outcome configurations: 1) knowledge and authority to respond to an unmet need; 2) role relevant training and opportunities for reflection; 3) clinical experts and senior staff promoting practices that are patient-focused; 4) engaging with opportunities to spend time with patients; 5) risk management as an opportunity for person-centred care; 6) valuing dementia care as skilled work. Effective interactions reduced patient distress and supported patient orientation. Training and allocation of staff time were of themselves insufficient to ensure dementia care was prioritised and valued as skilled work. Staff concerns about the consequences of adverse incidents and work pressures on the ward, even with support, took precedence and influenced the quality of their interactions with patients with dementia. A key finding linked to staff retention and developing capacity in the workforce to provide expert dementia care was that despite extra training and organisational endorsement, nursing staff did not regard dementia care as skilled nursing work. Conclusions: There is increased awareness and organisational commitment to dementia-friendly healthcare in general hospitals. However, in addition to training and adapting the environment to the patient, further work is needed to make explicit the specialist skills required for effective dementia care.Peer reviewe

On the dependability and feasibility of layperson ratings of divergent thinking

A new system for subjective rating of responses to divergent thinking tasks was tested using raters recruited from Amazon Mechanical Turk. The rationale for the study was to determine if such raters could provide reliable (aka generalizable) ratings from the perspective of generalizability theory. To promote reliability across the Alternative Uses and Consequence task prompts often used by researchers as measures of Divergent Thinking, two parallel scales were developed to facilitate feasibility and validity of ratings performed by laypeople. Generalizability and dependability studies were conducted separately for two scoring systems: the average-rating system and the snapshot system. Results showed that it is difficult to achieve adequate reliability using the snapshot system, while good reliability can be achieved on both task families using the average-rating system and a specific number of items and raters. Additionally, the construct validity of the average-rating system is generally good, with less validity for certain Consequences items. Recommendations for researchers wishing to adopt the new scales are discussed, along with broader issues of generalizability of subjective creativity ratings. © 2018 Hass, Rivera and Silvia

Artificial Intelligence And Big Data Technologies To Close The Achievement Gap.

We observe achievement gaps even in rich western countries, such as the UK, which in principle have the resources as well as the social and technical infrastructure to provide a better deal for all learners. The reasons for such gaps are complex and include the social and material poverty of some learners with their resulting other deficits, as well as failure by government to allocate sufficient resources to remedy the situation. On the supply side of the equation, a single teacher or university lecturer, even helped by a classroom assistant or tutorial assistant, cannot give each learner the kind of one-to-one attention that would really help to boost both their motivation and their attainment in ways that might mitigate the achievement gap. In this chapter Benedict du Boulay, Alexandra Poulovassilis, Wayne Holmes, and Manolis Mavrikis argue that we now have the technologies to assist both educators and learners, most commonly in science, technology, engineering and mathematics subjects (STEM), at least some of the time. We present case studies from the fields of Artificial Intelligence in Education (AIED) and Big Data. We look at how they can be used to provide personalised support for students and demonstrate that they are not designed to replace the teacher. In addition, we also describe tools for teachers to increase their awareness and, ultimately, free up time for them to provide nuanced, individualised support even in large cohorts

An audit of dressing practice by occupational therapists in acute stroke settings in England

Introduction Dressing independence is commonly affected after stroke, with clinical guidelines recommending that dressing practice should routinely be provided for those with dressing difficulties. The aim of this study was to update the literature on current practice in the treatment of dressing problems in stroke rehabilitation units. Method A questionnaire survey of occupational therapists experienced in stroke care was sent to 157 stroke units in England. Results Responses were received from 70 stroke units. Frequency and duration of dressing practice varied substantially between units, with respondents typically providing dressing practice for six to 10 patients per week and spending 30 to 45 minutes per treatment session. Only 17 respondents (24.3%) stated that they regularly used standardised assessments of dressing ability. The functional approach was used more widely than the remedial approach. Service priorities, working environment and limitations of time and staffing were reported to influence dressing practice. Conclusion There is widespread variability in dressing practice. There is a lack of use of standardised dressing assessments, and therapists’ rationale for their choice of approach is unclear