@misc{FehrJaramilloGutierrezOalaetal.2022, author = {Fehr, Jana and Jaramillo-Gutierrez, Giovanna and Oala, Luis and Gr{\"o}schel, Matthias I. and Bierwirth, Manuel and Balachandran, Pradeep and Werneck-Leite, Alixandro and Lippert, Christoph}, title = {Piloting a Survey-Based Assessment of Transparency and Trustworthiness with Three Medical AI Tools}, series = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Reihe der Digital Engineering Fakult{\"a}t}, journal = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Reihe der Digital Engineering Fakult{\"a}t}, number = {15}, doi = {10.25932/publishup-58328}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-583281}, pages = {30}, year = {2022}, abstract = {Artificial intelligence (AI) offers the potential to support healthcare delivery, but poorly trained or validated algorithms bear risks of harm. Ethical guidelines stated transparency about model development and validation as a requirement for trustworthy AI. Abundant guidance exists to provide transparency through reporting, but poorly reported medical AI tools are common. To close this transparency gap, we developed and piloted a framework to quantify the transparency of medical AI tools with three use cases. Our framework comprises a survey to report on the intended use, training and validation data and processes, ethical considerations, and deployment recommendations. The transparency of each response was scored with either 0, 0.5, or 1 to reflect if the requested information was not, partially, or fully provided. Additionally, we assessed on an analogous three-point scale if the provided responses fulfilled the transparency requirement for a set of trustworthiness criteria from ethical guidelines. The degree of transparency and trustworthiness was calculated on a scale from 0\% to 100\%. Our assessment of three medical AI use cases pin-pointed reporting gaps and resulted in transparency scores of 67\% for two use cases and one with 59\%. We report anecdotal evidence that business constraints and limited information from external datasets were major obstacles to providing transparency for the three use cases. The observed transparency gaps also lowered the degree of trustworthiness, indicating compliance gaps with ethical guidelines. All three pilot use cases faced challenges to provide transparency about medical AI tools, but more studies are needed to investigate those in the wider medical AI sector. Applying this framework for an external assessment of transparency may be infeasible if business constraints prevent the disclosure of information. New strategies may be necessary to enable audits of medical AI tools while preserving business secrets.}, language = {en} } @article{FehrJaramilloGutierrezOalaetal.2022, author = {Fehr, Jana and Jaramillo-Gutierrez, Giovanna and Oala, Luis and Gr{\"o}schel, Matthias I. and Bierwirth, Manuel and Balachandran, Pradeep and Werneck-Leite, Alixandro and Lippert, Christoph}, title = {Piloting a Survey-Based Assessment of Transparency and Trustworthiness with Three Medical AI Tools}, series = {Healthcare}, volume = {10}, journal = {Healthcare}, number = {10}, publisher = {MDPI}, address = {Basel, Schweiz}, issn = {2227-9032}, doi = {10.3390/healthcare10101923}, pages = {30}, year = {2022}, abstract = {Artificial intelligence (AI) offers the potential to support healthcare delivery, but poorly trained or validated algorithms bear risks of harm. Ethical guidelines stated transparency about model development and validation as a requirement for trustworthy AI. Abundant guidance exists to provide transparency through reporting, but poorly reported medical AI tools are common. To close this transparency gap, we developed and piloted a framework to quantify the transparency of medical AI tools with three use cases. Our framework comprises a survey to report on the intended use, training and validation data and processes, ethical considerations, and deployment recommendations. The transparency of each response was scored with either 0, 0.5, or 1 to reflect if the requested information was not, partially, or fully provided. Additionally, we assessed on an analogous three-point scale if the provided responses fulfilled the transparency requirement for a set of trustworthiness criteria from ethical guidelines. The degree of transparency and trustworthiness was calculated on a scale from 0\% to 100\%. Our assessment of three medical AI use cases pin-pointed reporting gaps and resulted in transparency scores of 67\% for two use cases and one with 59\%. We report anecdotal evidence that business constraints and limited information from external datasets were major obstacles to providing transparency for the three use cases. The observed transparency gaps also lowered the degree of trustworthiness, indicating compliance gaps with ethical guidelines. All three pilot use cases faced challenges to provide transparency about medical AI tools, but more studies are needed to investigate those in the wider medical AI sector. Applying this framework for an external assessment of transparency may be infeasible if business constraints prevent the disclosure of information. New strategies may be necessary to enable audits of medical AI tools while preserving business secrets.}, language = {en} } @article{EweltKnauerSchweringWinkelmann2021, author = {Ewelt-Knauer, Corinna and Schwering, Anja and Winkelmann, Sandra}, title = {Probabilistic audits and misreporting}, series = {European accounting review}, volume = {30}, journal = {European accounting review}, number = {5}, publisher = {Routledge}, address = {London}, issn = {1468-4497}, doi = {10.1080/09638180.2021.1899014}, pages = {989 -- 1012}, year = {2021}, abstract = {We investigate how the design of audit processes influences employees' reporting decisions. We focus specifically on detective employee audits for which several employees are randomly selected after a defined period to audit their ex-post behavior. We investigate two design features of the audit process, namely, employee anonymity and process transparency, and analyze their impact on misreporting. Overall, we find that both components influence the extent of individuals' misreporting. A nonanonymous audit decreases performance misreporting more than an audit in which the employee remains anonymous. Furthermore, the high incidence of performance misreporting in the case of anonymous audits can be decreased when the process transparency is low. Thus, our study informs accountants about how the two design features of employee anonymity and transparency of the audit process can be used to constrain performance misreporting to increase the efficiency of audits}, language = {en} } @techreport{OPUS4-4236, type = {Working Paper}, title = {Tax systems and tax harmonisation in the East African Community (EAC)}, series = {Finanzwissenschaftliche Diskussionsbeitr{\"a}ge}, journal = {Finanzwissenschaftliche Diskussionsbeitr{\"a}ge}, number = {60}, editor = {Petersen, Hans-Georg}, issn = {1864-1431}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-44693}, pages = {128}, year = {2010}, abstract = {In the first part of the report of the GTZ expert group an overview on the basics of integration and tax harmonisation within a common market is given. Chapter II. concentrates on the problems of national and international tax law regarding double taxation before the harmonisation process within the EU is described in detail. This process is not a best practice example but at least the experiences made in the course of the last five decades are interesting enough and might contribute important information for regions, which more or less recently have started a similar endeavour. The harmonisation needs are discussed for value added taxation (VAT), excise taxation, and income taxation. The problems of tax administrations, procedures laws, taxpayers' rights and obligations as well as tax compliance are also taken into consideration. The second part of the study reviews the national tax systems within the EAC member countries. Before the single taxes are described in more detail, the macroeconomic situation is illuminated by some basic figures and the current stand of the inner-community integration analysed. Then the single tax bases and tax rates are confronted to shed some light on the necessities for the development of a common market within the near future. Again the value added tax laws, excise taxes and income taxes are discussed in detail, while regarding the latter the focus is on company taxation. For a better systematic analysis the national tax laws are confronted within an overview. The chapter is closed with a summary of the tax rates applied and a rough estimation of the tax burdens within the Partner States. The third part of this report contains the policy recommendations of the expert group following the same structures as the chapters before and presenting the results for the VAT, the excises and the corporate income tax (CIT). Additionally the requirements for tax procedures and administration as well as problems of transparency and information exchange are discussed in detail before the strategic recommendations are derived in close relation to the experiences made within the EU harmonisation process. The recommendations are based on the following normative arguments: (1) Tax harmonisation is a basic requirement for economic integration. (2) Equality of taxation is an imperative of tax justice and demands the avoidance of double taxation as well as the combat of tax evasion and corruption. (3) The avoidance of harmful tax competition between the Partner States. (4) The strengthening of taxpayers' rights in tax procedures. Hence, all kinds of income, goods and services should be taxed once and only once.}, language = {en} }