More and more complex semi-automated systems are being developed, aiding human operators to collect and analyze data and information and even to recommend decisions and act upon these. The goal of such development is often to support the operators make better decisions faster, while at the same time decrease their workload. However, these promises are not always fulfilled and several incidents have highlighted the fact that the introduction of automated technologies might instead increase the need for human involvement andexpertise in the tasks carried out. The significance of communicating information regarding an automated system's performance and to explain its strengths and limitations to its operators is strongly highlighted within the system transparencyand operator-centered automation literature. However, it is not common that feedback containing system qualifiers is incorporated into the primary displays of the automated system, obscuring its transparency. In this thesis, we deal with the investigation of the effects of explaining and visualizing system reasoning and performance parameters in different domains on the operators' trust, workload and performance. Different proof-of-concept prototypes have been designed with transparency characteristics in mind, and quantitative and qualitative evaluations together with operators of these systems have been carried out. Our results show that the effects of automation transparency can positively influence the performance and trust calibration of operators of complex systems, yet possibly at the costs of higher workload and longer decision-making times. Further, this thesis provides recommendations for designers and developers of automated systems in terms of general design concepts and guidelines for developing transparent automated systems for the future. / Fler och fler komplexa semiautomatiserade system utvecklas idag, vilka hjälper operatörer att samla in och analysera data och information och även att rekommendera beslut och agera på dessa. Det yttersta målet med implementeringen av automatiserade system är ofta att hjälpa operatörerna att fatta bättre beslut snabbare och samtidigt minska deras arbetsbelastning. Dock blir detta inte alltid fallet och flera olyckor har uppmärksammat faktumet att introduktionen av automatiserade system istället kan öka behovet av mänsklig inblandning och expertis. Inom forskningsområden såsom automationstransparens och operatörscentrerad automation har vikten av att kommunicera information angående automationens prestanda betonats, likaså att förklara dess styrkor och svagheter för operatörerna. Dock är det inte vanligt att sådan meta-information inkorporeras i de automatiska systemens primära användargränssnitt, vilket kan försvåra det för operatörerna att tillgodogöra sig denna information. I denna avhandling undersöks effekterna av att förklara och visualisera semiautomatiserade systems resonerande och prestanda i olika domäner på operatörernas tillit till systemen, deras upplevda arbetsbörda och deras prestation. Olika konceptprototyper har designats med inkorporerade transparensegenskaper och kvalitativa och kvantitativa utvärderingar tillsammans med operatörer av dessa system har genomförts. Resultaten visar att automationstransparens kan ha positiva effekter på operatörers prestanda och tillitskalibrering, dock med möjliga kostnader i form av högre upplevd arbetsbelastning och längre beslutstider. Avhandlingen erbjuder även rekommendationer till designers och utvecklare i form av generella riktlinjer och designegenskaper vid utvecklandet av framtida transparenta semiautomatiserade stödsystem. / <p>The author is also affiliated to the university of Skövde</p><p>This research has been founded by The Swedish Governmental Agency for InnovationSystems (Vinnova) through the National Aviation Engineering Research Program(NFFP5-2009-01315) and supported by Saab AB.</p>

Dans le cadre de ma thèse, je me demande à quelles conditions le travail en groupe peut être le catalyseur susceptible de réduire les biais de raisonnement prégnants au niveau individuel. Particulièrement, je m’intéresse à l’heuristique de représentativité.Je réponds à cette question en m’inspirant du paradigme du partage des informations. Selon celui-ci, les membres des groupes ne partagent pas leurs informations uniques. Je postule qu’amener les groupes à discuter les informations pertinentes à la résolution du problème est le critère minimum, et peut-être suffisant pour garantir des performances de raisonnement optimales. J’ai pensé que ça pourrait être le cas si les participants disposaient de méta-informations les informant sur la distribution des informations au sein du groupe. Six études examinent le rôle des méta-informations sur la réduction des biais dans le raisonnement en groupe. Les résultats des 3 premières études mettent en évidence l’effet positif des méta-informations sur le travail en groupe.Dans les 3 études suivantes, je nuance le degré de généralité des conclusions antérieures. Mes résultats indiquent que les estimations individuelles préalables au travail en groupe peuvent elles aussi être affectées par la présence de méta-informations. De plus, celles-ci colorent la perception des membres du groupe quant à la pertinence des données uniques qu’elles désignent, les amenant à des raisonnements biaisés si ces données ne sont pas pertinentes. Enfin, l’effet des méta-informations sur le partage n’est pas positif à tous les coups : Si la coopération maximise leur effet, celui-ci est délétère lorsque la compétition règne parmi les membres du groupe. / Within my thesis’ framework, I asked myself under what conditions group-work could constitute a catalyst likely to reduce biases in individual reasoning. Particularly, my attention was drawn to the heuristic of representativeness. I answered this question through the lens of the information sharing paradigm. These authors showed that group members do not pool unshared information. Such statement led me to an unseemly question. If group members do not share information that is indispensable to solve a problem, by what means would they succeed avoiding reasoning pitfalls? Also, I stated that to bring groups over “discussing all information that is pertinent to the problem’s resolution” was the bare minimum criteria to succeed and it was maybe enough to guarantee satisfying reasoning performances. I predicted that it might be the case if participants had available meta-information. A total of six studies examine the role of meta-information on reducing biases within group thinking. The results from the first 3 studies underline the positive effect of meta-information.In the subsequent 3 studies, I scrutinize the generalities previously stated. Results also point to individual and previous-to-work estimations being affected by meta-information. Furthermore, meta-information colors group members’ perception regarding the pertinence of the unshared data it assigns, leading them to biased reasoning, when such data is not relevant. Finally, meta-information’s effect on information sharing is not always positive : it becomes deleterious once competition takes over group members.

More and more complex semi-automated systems are being developed, aiding human operators to collect and analyze data and information and even to recommend decisions and act upon these. The goal of such development is often to support the operators make better decisions faster, while at the same time decrease their workload. However, these promises are not always fulfilled and several incidents have highlighted the fact that the introduction of automated technologies might instead increase the need for human involvement andexpertise in the tasks carried out. The significance of communicating information regarding an automated system's performance and to explain its strengths and limitations to its operators is strongly highlighted within the system transparencyand operator-centered automation literature. However, it is not common that feedback containing system qualifiers is incorporated into the primary displays of the automated system, obscuring its transparency. In this thesis, we deal with the investigation of the effects of explaining and visualizing system reasoning and performance parameters in different domains on the operators' trust, workload and performance. Different proof-of-concept prototypes have been designed with transparency characteristics in mind, and quantitative and qualitative evaluations together with operators of these systems have been carried out. Our results show that the effects of automation transparency can positively influence the performance and trust calibration of operators of complex systems, yet possibly at the costs of higher workload and longer decision-making times. Further, this thesis provides recommendations for designers and developers of automated systems in terms of general design concepts and guidelines for developing transparent automated systems for the future.

京都大学 / 新制・課程博士 / 博士(情報学) / 甲第24729号 / 情博第817号 / 新制||情||137(附属図書館) / 京都大学大学院情報学研究科知能情報学専攻 / (主査)教授 河原 達也, 教授 黒橋 禎夫, 教授 森 信介 / 学位規則第4条第1項該当 / Doctor of Informatics / Kyoto University / DFAM

Data integration techniques are one of the core elements of DIECOFIS, an EU-funded international research project that aims at developing a methodology for the construction of a system of indicators on competitiveness and fiscal impact on enterprise performance. Data integration is also of major interest for official statistics agencies as a means of using available information more efficiently and improving the quality of the agency's products. The Austrian member of the project consortium comprises university departments, representatives from the Bundesanstalt Statistik Austria, from the Statistical Department of the Austrian Economic Chamber, and from ec3, a non-profit research corporation. This paper gives a short report on DIECOFIS in general and on the Austrian contribution to the project, mainly dealing with data integration methodology. Various papers that have been read at the DIECOFIS workshop last November in Vienna, will be published as a Special Issue of the Austrian Journal of Statistics.