A global perspective on data powering responsible AI solutions in health applications

@article{Rudd2023AGP,
  title={A global perspective on data powering responsible AI solutions in health applications},
  author={Jessica M. Rudd and Claudia Igbrude},
  journal={Ai and Ethics},
  year={2023},
  pages={1 - 11},
  url={https://api.semanticscholar.org/CorpusID:259016605}
}
This review suggests consideration of a more global perspective, with a particular focus on marginalized communities, during the development of healthcare AI solutions, to better capture the needs of a global population.
View on PubMed
link.springer.com
13 Citations
Background Citations
2

13 Citations

Transforming Healthcare with AI: Promises, Pitfalls, and Pathways Forward

The paper explores the challenges posed by data privacy concerns, algorithmic biases, and ensuring equitable access to AI-driven healthcare, and advocates for the development of comprehensive ethical frameworks and ongoing research to guide the responsible use of AI in healthcare.

AI and omics technologies in biobanking: Applications and challenges for public health.

The What, So What, and What Now of the AI Landscape in Emerging Economies

The state of integration and challenges impeding the adoption of AI in the Global South are explored, and targeted recommendations for policymakers, academia, entrepreneurs, and NGOs to tailor AI solutions to local needs to address these barriers and enhance economic and social equity are offered.

Human-Data Interaction Framework: A Comprehensive Model for a Future Driven by Data and Humans

The fundamental steps required for organizations to seamlessly integrate HDI principles are outlined, emphasizing auditing, aligning, formulating considerations, and the need for continuous monitoring and adaptation.

Systematic review of ethics and legislation of a Global Patient co-Owned Cloud (GPOC)

This study suggests that GPOC could potentially establish a new human right to patient co-ownership of personal health information globally, and presents a global overview of the relevant global latticework of legislation.

Assessing AI literacy and attitudes among medical students: implications for integration into healthcare practice

The study revealed varying levels of AI literacy among medical students with a basic understanding of AI principles, highlighting the need for targeted educational interventions and ethical considerations in AI integration within medical education and practice.

A review of caveats and future considerations of research on responsible AI across disciplines

Using grounded theory and axial and open coding, areas, principles, research designs, challenges, findings, and trends in responsible AI research across the emerging areas are extracted.

State-of-the-Art in Responsible, Explainable, and Fair AI for Medical Image Analysis

The following review provides a concise overview of REF-AI in the context of medical image analysis, beginning with the fundamental concepts of AI responsibility, explainability, and fairness, followed by a comprehensive taxonomy of over 35 key algorithms and strategies.

Transformative potential of artificial intelligence in global health policy

ChatGPT is a promising AI technology that can revolutionize global health policy, enabling vital contributions to complex decision-making processes at all levels of government agencies and can facilitate communication between humans and machines.

AI-Powered Techniques in Anatomical Imaging: Impacts on Veterinary Diagnostics and Surgery.

45 References

Challenges and Potential Solutions for Big Data Implementations in Developing Countries

The challenges developing countries would face and enumerate the options to be used to achieve successful implementations of Big Data programs are described.

Artificial intelligence (AI) and global health: how can AI contribute to health in resource-poor settings?

A general overview of AI and how it can be used to improve health outcomes in resource-poor settings is provided and some of the current ethical debates around patient safety and privacy are described.

Precision medicine: opportunities, possibilities, and challenges for patients and providers

Several ethical, legal, and social issues related to the Precision Medicine Initiative's proposed changes to current institutions, values, and frameworks are outlined.

Artificial Intelligence for Healthcare in Africa

Digital technology will play a significant role in achieving sustainable human development worldwide. In 2015, United Nations Member States set 17 goals, the Sustainable Development Goals (SDGs), to…

Ethical and legal challenges of artificial intelligence-driven healthcare

This chapter will map the ethical and legal challenges posed by artificial intelligence (AI) in healthcare and suggest directions for resolving them and emphasize the importance of building an AI-driven healthcare system that is successful and promotes trust and the motto Health AIs for All of Us.

Comparative analyses of population-scale phenomic data in electronic medical records reveal race-specific disease networks

This work is the first attempt to perform comparative, population-scale analyses of disease networks across three different populations, namely Caucasian, African American and Hispanic/Latino, and revealed appreciable differences in disease susceptibility, temporal patterns, network structure and underlying disease connections between EA, AA and HL populations.

Missed policy opportunities to advance health equity by recording demographic data in electronic health records.

An administrative history of HITECH was conducted and gaps between the policy objective and required measure were identified, identifying 20 opportunities for change and 5 changes, 2 of which required the collection of less data.

Generation and evaluation of synthetic patient data

This paper evaluates three classes of synthetic data generation approaches; probabilistic models, classification-based imputation models, and generative adversarial neural networks and discusses the trade-offs of the different methods and metrics, providing guidance on considerations for the generation and usage of medical synthetic data.

Sex and gender differences and biases in artificial intelligence for biomedicine and healthcare

The current sex and gender gaps in a subset of biomedical technologies used in relation to Precision Medicine are examined and recommendations to optimize their utilization are provided to improve the global health and disease landscape and decrease inequalities.

What is data ethics?

Developing data ethics from the start as a macroethics, that is, as an overall framework that avoids narrow, ad hoc approaches and addresses the ethical impact and implications of data science and its applications within a consistent, holistic and inclusive framework.