Judicial Artificial Intelligence Bias: A Survey and Recommendations

2021 ◽  
Vol 9 (2) ◽  
pp. 74-86
Author(s):  
Ogochukwu Constance Ngige ◽  
Oludele Awodele ◽  
Oluwatobi Balogun
Keyword(s):  
Artificial Intelligence ◽  
Energy Transport ◽  
Human Existence ◽  
Professional Life ◽  
Human Society ◽  
Close Attention ◽  
Artificial Intelligence System ◽  
Intelligence System ◽  
Almost All ◽  
The Way

Artificial intelligence (AI) has continued to disrupt the way tasks are being carried out, finding its way into almost all facets of human existence, and advancing the development of human society. The AI revolution has made huge and significant inroad into diverse industries like health, energy, transport, retail, advertising, et cetera. AI has been found to assist in carrying out tasks more quickly and efficiently too. Tasks which were hitherto difficult have been simplified significantly through the use of AI. Slow adoption in judiciary has however been reported, compared to other sectors. A lot of factors have been attributed to this, with AI bias being an issue of concern. Decisions emanating from courts have a significant impact on an individual’s private and professional life. It is thus imperative to identify and deal with bias in any judicial AI system in order to avoid delivering a prejudiced and inaccurate decision, thereby possibly intensifying the existing disparities in the society. This paper therefore surveys judicial artificial intelligence bias, paying close attention to types and sources of AI bias in judiciary. The paper also studies the trust-worthy AI, the qualities of a trust-worthy artificial intelligence system and the expectations of users as it is being deployed to the judiciary, and concludes with recommendations in order to mitigate the AI bias in Judiciary.

330 DEVELOPMENT AND VALIDATION OF AN ARTIFICIAL INTELLIGENCE SYSTEM TO OPTIMIZE CLINICIAN REVIEW OF PATIENT RECORDS

2021 ◽  
Vol 160 (6) ◽  
pp. S-64-S-65
Author(s):  
Ethan A. Chi ◽  
Gordon Chi ◽  
Cheuk To Tsui ◽  
Yan Jiang ◽  
Karolin Jarr ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Patient Records ◽  
Artificial Intelligence System ◽  
Intelligence System ◽  
Development And Validation

scholarly journals COVID-19-induced vascular angiopathy: CTPA signs in critically ill patients other than acute pulmonary embolism and high-lung opacity scores

2021 ◽  
Vol 52 (1) ◽  
Author(s):  
Mohamed Hossameldin khalifa ◽  
Ahmed Samir ◽  
Ayman Ibrahim Baess ◽  
Sara Samy Hendawi
Keyword(s):  
Artificial Intelligence ◽  
Pulmonary Embolism ◽  
Lung Volume ◽  
Acute Pulmonary Embolism ◽  
Pulmonary Angiography ◽  
Vascular Tree ◽  
Ct Pulmonary Angiography ◽  
Artificial Intelligence System ◽  
Intelligence System ◽  
Severity Scores

Abstract Background Vascular angiopathy is suggested to be the major cause of silent hypoxia among COVID-19 patients without severe parenchymal involvement. However, pulmonologists and clinicians in intensive care units become confused when they encounter acute respiratory deterioration with neither severe parenchymal lung involvement nor acute pulmonary embolism. Other radiological vascular signs might solve this confusion. This study investigated other indirect vascular angiopathy signs on CT pulmonary angiography (CTPA) and involved a novel statistical analysis that was performed to determine the significance of associations between these signs and the CT opacity score of the pathological lung volume, which is calculated by an artificial intelligence system. Results The study was conducted retrospectively, during September and October 2020, on 73 patients with critical COVID-19 who were admitted to the ICU with progressive dyspnea and low O2 saturation on room air (PaO2 < 93%). They included 53 males and 20 females (73%:27%), and their age ranged from 18 to 88 years (mean ± SD=53.3 ± 13.5). CT-pulmonary angiography was performed for all patients, and an artificial intelligence system was utilized to quantitatively assess the diseased lung volume. The radiological data were analyzed by three expert consultant radiologists to reach consensus. A low CT opacity score (≤10) was found in 18 patients (24.7%), while a high CT opacity score (>10) was found in 55 patients (75.3%). Pulmonary embolism was found in 24 patients (32.9%); three of them had low CT opacity scores. Four other indirect vasculopathy CTPA signs were identified: (1) pulmonary vascular enlargement (57 patients—78.1%), (2) pulmonary hypertension (14 patients—19.2%), (3) vascular tree-in-bud pattern (10 patients—13.7%), and (4) pulmonary infarction (three patients—4.1%). There were no significant associations between these signs and the CT opacity score (0.3205–0.7551, all >0.05). Furthermore, both pulmonary vascular enlargement and the vascular tree-in-bud sign were found in patients without pulmonary embolism and low CT-severity scores (13/15–86.7% and 2/15–13.3%, respectively). Conclusion Pulmonary vascular enlargement or, less commonly, vascular tree-in-bud pattern are both indirect vascular angiopathy signs on CTPA that can explain the respiratory deterioration which complicates COVID-19 in the absence of severe parenchymal involvement or acute pulmonary embolism.

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