Is There a Trade-Off Between Human Autonomy and the ‘Autonomy’ of AI Systems?

Autonomy is often considered a core value of Western society that is deeply entrenched in moral, legal, and political practices. The development and deployment of artificial intelligence (AI) systems to perform a wide variety of tasks has raised new questions about how AI may affect human autonomy. Numerous guidelines on the responsible development of AI now emphasise the need for human autonomy to be protected. In some cases, this need is linked to the emergence of increasingly ‘autonomous’ AI systems that can perform tasks without human control or supervision. Do such ‘autonomous’ systems pose a risk to our own human autonomy? In this article, I address the question of a trade-off between human autonomy and system ‘autonomy’

Transportation barriers to care among frequent health care users during the COVID pandemic

Background: Transportation problems are known barriers to health care and can result in late arrivals and delayed or missed care. Groups already prone to greater social and economic disadvantage, including low-income individuals and people with chronic conditions, encounter more transportation barriers and experience greater negative health care consequences. Addressing transportation barriers is important not only for mitigating adverse health care outcomes among patients, but also for avoiding additional costs to the health care system. In this study, we investigate transportation barriers to accessing health care services during the COVID-19 pandemic among high-frequency health care users. Methods: A web-based survey was administered to North Carolina residents aged 18 and older in the UNC Health system who were enrolled in Medicaid or Medicare and had at least six outpatient medical appointments in the past year. 323 complete responses were analyzed to investigate the prevalence of reporting transportation barriers that resulted in having arrived late to, delayed, or missed care, as well as relationships between demographic and other independent variables and transportation barriers. Qualitative analyses were performed on text response data to explain transportation barriers. Results: Approximately 1 in 3 respondents experienced transportation barriers to health care between June 2020 and June 2021. Multivariate logistic regressions indicate individuals aged 18–64, people with disabilities, and people without a household vehicle were significantly more likely to encounter transportation barriers. Costs of traveling for medical appointments and a lack of driver or car availability emerged as major transportation barriers; however, respondents explained that barriers were often complex, involving circumstantial problems related to one’s ability to access and pay for transportation as well as to personal health. Conclusions: To address transportation barriers, we recommend more coordination between transportation and health professionals and the implementation of programs that expand access to and improve patient awareness of health care mobility services. We also recommend transportation and health entities direct resources to address transportation barriers equitably, as barriers disproportionately burden younger adults under age 65 enrolled in public insurance programs

Human autonomy in the age of artificial intelligence

Current AI policy recommendations differ on what the risks to human autonomy are. To systematically address risks to autonomy, we need to confront the complexity of the concept itself and adapt governance solutions accordingly

Algorithmic profiling as a source of hermeneutical injustice

This is the author accepted manuscriptIt is well-established that algorithms can be instruments of injustice. It is less frequently discussed, however, how current modes of AI deployment often make the very discovery of injustice difficult, if not impossible. In this article, we focus on the effects of algorithmic profiling on epistemic agency. We show how algorithmic profiling can give rise to epistemic injustice through the depletion of epistemic resources that are needed to interpret and evaluate certain experiences. By doing so, we not only demonstrate how the philosophical conceptual framework of epistemic injustice can help pinpoint potential, systematic harms from algorithmic profiling, but we also identify a novel source of hermeneutical injustice that to date has received little attention in the relevant literature: epistemic fragmentation. As we explain below, epistemic fragmentation is a structural characteristic of algorithmically-mediated environments that isolate individuals, making it more difficult to develop, uptake and apply new epistemic resources. This, in turn, can impede the identification and conceptualisation of emerging harms in these environments. We trace the occurrence of hermeneutical injustice back to the fragmentation of the epistemic experiences of individuals, who are left more vulnerable by the inability to share, compare, and learn from shared experiences

Institutionalizing ethics in AI through broader impact requirements

Turning principles into practice is one of the most pressing challenges of artificial intelligence (AI) governance. In this Perspective, we reflect on a governance initiative by one of the world’s largest AI conferences. In 2020, the Conference on Neural Information Processing Systems (NeurIPS) introduced a requirement for submitting authors to include a statement on the broader societal impacts of their research. Drawing insights from similar governance initiatives, including institutional review boards (IRBs) and impact requirements for funding applications, we investigate the risks, challenges and potential benefits of such an initiative. Among the challenges, we list a lack of recognized best practice and procedural transparency, researcher opportunity costs, institutional and social pressures, cognitive biases and the inherently difficult nature of the task. The potential benefits, on the other hand, include improved anticipation and identification of impacts, better communication with policy and governance experts, and a general strengthening of the norms around responsible research. To maximize the chance of success, we recommend measures to increase transparency, improve guidance, create incentives to engage earnestly with the process, and facilitate public deliberation on the requirement’s merits and future. Perhaps the most important contribution from this analysis are the insights we can gain regarding effective community-based governance and the role and responsibility of the AI research community more broadly

Optical, Redox, and DNA Binding Properties of Phenanthridium Chromophores: Elucidating the Role of the Phenyl Substituent for Fluorescence Enhancement of Ethidium in the Presence of DNA

The phenanthridinium chromophores 5-ethyl-6-phenylphenanthridinium (1), 5-ethyl-6-methylphenanthridinium (2), 3,8-diamino-5-ethyl-6-methylphenanthridinium (3), and 3,8-diamino-5-ethyl-6-(4-N,N-diethylaminophenyl)phenanthridinium (4) were characterized by their optical and redox properties. All dyes were applied in titration experiments with a random-sequence 17mer DNA duplex and their binding affinities were determined. The results were compared to well-known ethidium bromide (E). In general, this set of data allows the influence of substituents in positions 3, 6, and 8 on the optical properties of E to be elucidated. Especially, compound 4 was used to compare the weak electron-donating character of the phenyl substituent at position 6 of E with the more electron-donating 4-N,N-diethylaminophenyl group. Analysis of all of the measurements revealed two pairs of chromophores. The first pair, consisting of 1 and 2, lacks the amino groups in positions 3 and 8, and, as a result, these dyes exhibit clearly altered optical and electrochemical properties compared with E. In the presence of DNA, a significant fluorescence quenching was observed. Their binding affinity to DNA is reduced by nearly one order of magnitude. The electronic effect of the phenyl group in position 6 on this type of dye is rather small. The properties of the second set, 3 and 4, are similar to E due to the presence of the two strongly electron-donating amino groups in positions 3 and 8. However, in contrast to 1 and 2, the electron-donating character of the substituent in position 6 of 3 and 4 is critical. The binding, as well as the fluorescence enhancement, is clearly related to the electron-donating effect of this substituent. Accordingly, compound 4 shows the strongest binding affinity and the strongest fluorescence enhancement. Quantum chemical calculations reveal a general mechanism related to the twisted intramolecular charge transfer (TICT) model. Accordingly, an increase of the twist angle between the phenyl ring in position 6 and the phenanthridinium core opens a nonradiative channel in the excited state that depends on the electron-donating character of the phenyl group. Access to this channel is hindered upon binding to DNA