A Case Study on the use of AI regarding ethics and analysis customer feedback

Renewing healthcare applications with AI

A company has established itself as an innovative force in the digital health field, specializing in the development of mobile applications aimed at enriching patient wellbeing and care management. Despite a promising start, the company faced challenges in terms of user engagement and matching functionality to patient expectations. To meet these challenges, it made the strategic choice of integrating artificial intelligence into its customer feedback evaluation and analysis process.

The company’s aim was to comprehensively capture and analyze user feedback to guide the development of functionalities and improve the user experience. Given the sheer volume of feedback data, including qualitative comments and quantitative usage metrics, identifying trends and preferences became crucial.

To achieve this, it created an AI solution designed to :

• Collect user feedback via a variety of channels, including reviews on app platforms, comments on social networks and integrated surveys.
• Use natural language processing and machine learning to decipher reasons for satisfaction or dissatisfaction, suggestions for improvement and usage trends.
• Prioritize product updates and innovations based on the relevance and recurrence of feedback, considering technical feasibility and impact on user experience.
• Offer interactive dashboards to development and product management teams, for real-time monitoring of user insights.

Integrated into the product development lifecycle,the AI solution informed the design, development and update stages of applications with regular analyses.

The results were transformative :

• Improved User Engagement: Apps updated based on feedback analysis have seen an increase in user engagement and satisfaction.
• Targeted innovations: Precise detection of user expectations has enabled the development of innovations and features that specifically meet patients’ needs.
• Increased market responsiveness: Rapid feedback analysis has strengthened the company’s ability to respond to user requests, improving its position in the healthcare app market.
• Positive Impact on Health: Optimized applications have promoted better management of users’ health, underlining the effectiveness of integrating AI into customer feedback processing.

Key Insights: The company’s journey underscores the pivotal role of Artificial Intelligence in leveraging customer feedback within the digital health domain. Guiding product evolution through insightful analysis of feedback, the company has not only enhanced user engagement but also fueled innovation in its healthcare solutions. This strategy, backed by advanced AI technologies, showcases the transformative power of AI in redefining products and services to meet user demands and preferences effectively.

A Practical Case:

Ethical implementation of AI for customer feedback analysis in a teleconsultation clinic

A teleconsultation clinic, seeks to improve the quality of its services and patient experience by leveraging customer feedback. The clinic offers a wide range of remote healthcare services, including medical consultations, therapeutic follow-up and nutritional advice. Although overall satisfaction is high, the clinic is keen to identify specific areas for improvement and proactively address its patients’ needs and concerns.

The main challenge for the clinic is to efficiently process and analyze the large volumes of feedback gathered through various channels: satisfaction surveys, comments on the mobile app, post-consultation follow-up emails, and opinions on social networks. In addition, the company is deeply committed to respecting the ethics and data protection of its users, particularly with regard to the sensitivity of health information.

To meet this challenge, the clinic decided to develop an artificial intelligence system specifically designed to analyze customer feedback while strictly adhering to ethical principles and data protection regulations :

• Data collection:The solution collects feedback through the channels mentioned, ensuring that all data is anonymized before analysis to protect patients’ identities. Patients are informed about the use of their feedback for service improvement purposes and give their explicit consent for their data to be processed.
• Data processing and analysis :Use of advanced natural language processing techniques to identify recurring themes, specific concerns, and suggestions for improvement without ever accessing personally identifiable information. Application of machine learning algorithms to determine priorities for action based on the frequency and severity of feedback.
• Application of results:Insights generated by the solution are used to inform product development teams, healthcare professionals, and customer service on areas requiring improvement or adjustment. Setting up ethical dashboards for real-time monitoring of customer satisfaction and trends, while guaranteeing data confidentiality.

Implementation:

• Pilot phase with a restricted group of users to refine the solution’s algorithms and ensure their ethical and regulatory compliance.
• Training of in-house teams on the ethical principles guiding the use of the solution, including transparency, privacy and data integrity.
• Progressive roll-out to the entire user base, accompanied by clear communication of the clinic’s ethical commitment.

Results:

• Continuous improvement of the patient experience based on ethically analyzed data, leading to increased satisfaction and engagement.
• Enhanced user confidence through transparent and accountable feedback management.
• Enhanced ability of the clinic to anticipate and respond to the emerging healthcare needs of its patients, while respecting their privacy and autonomy.

Key learnings: This case study exemplifies the way in which ethical incorporation of Artificial Intelligence can empower a healthcare firm to utilize customer feedback for enhancing its offerings, all the while adhering to its ethical standards and maintaining users’ confidentiality expectations.

To find out more :

The paper “Operationalising AI ethics through the agile software development lifecycle: a case study of AI-enabled mobile health applications”, written by Mbangula Lameck Amugongo, PhD, Alexander Kriebitz, Auxane Boch, and Christoph Lütge of the Technical University of Munich, Institute for Artificial Intelligence Ethics, dated August 15, 2023, offers a detailed exploration of the integration of ethical principles into the agile development of AI-assisted mobile health (mHealth) applications. Here are the five main points highlighted:

• Ethical frameworks and principles: The analysis highlights the necessary transition from universal ethical principles to case-specific ethical frameworks, incorporating values such as fairness, agility, accuracy, respect, trust, responsibility, robustness and reproducibility.
• Ethics by design: The document advocates the proactive integration of ethical considerations from the earliest stages of AI development, ensuring that ethical challenges are addressed from conception and throughout the development lifecycle.
• Relational ethics and human values: The importance of relational ethics and respect for human values in AI development is emphasized, balancing individual rights and public health needs and ensuring the inclusion of diverse populations.
• Operationalization of ethical principles: A framework for the practical application of ethical principles is detailed, covering all phases of software development, from requirements gathering to deployment, to ensure a consistent ethical approach.
• Case studies and practical examples: Through concrete examples and case studies, the paper illustrates how the proposed ethical frameworks can be applied to the development of AI-assisted mHealth applications, highlighting the crucial role of ethics in improving quality of care and patient outcomes.

This research highlights the challenges and opportunities of integrating ethics into the agile development of healthcare technology solutions, offering a structured method for developing AI applications in a responsible and inclusive manner.

Link :

https://link.springer.com/article/10.1007/s43681-023-00331-3

Article written by Esteban MARTINEZ QUEROL