Recap: Uncovering the Security and Privacy Challenges in AI-powered Health Services

August 3rd, 2023 by Kendra Stansel

life sciences

On June 29, 2023, Inflectra hosted a panel discussion on Uncovering the Security and Privacy Challenges in AI-powered Health Services in continuation of our Influence of AI and ML Technologies - Expert Panel Series. This insightful conversation, that took between two of Inflectra's experts, focused on security vulnerabilities, privacy concerns, and liability for intellectual property related to the use of AI in the healthcare industry. Continue reading to see the key takeaways, recording, and more.

recap-blog-uncovering-the-security-and-privacy-challenges-in-ai-powered-health-services-inflectra-image

KEY TAKEAWAYS:

Organizations must address these risks and concerns to safely and ethically implement AI in the healthcare industry:

1. Elevating AI Knowledge and Preparedness in Healthcare:
    - Mastering AI in Healthcare: Grasping healthcare needs and challenges is vital when architecting AI-based systems. This knowledge plays a crucial role, particularly concerning data privacy, encapsulating confidentiality, integrity, and availability. AI education programs should blend technical training with crucial soft skills like systems-thinking and risk management, insists Dr. Sriram Rajagopalan from Inflectra. Simultaneously, it is essential to enhance the AI knowledge base of healthcare professionals and organizations.
    - AI Risk Contingency: As AI forges ahead, healthcare professionals must be equipped to identify and manage potential AI-linked prospects and risks. Proactive training in AI risk management is the cornerstone to fostering resilience in this dynamic healthcare environment.
    - Embracing AI Evolution in Healthcare: The ever-changing landscape of AI demands continuous adaptation. Developers should engage with emerging methodologies focusing on value management techniques, enabling healthcare teams to responsibly harness AI's potential.

2. Emphasizing Ethics and Patient-Centricity in AI Healthcare Development:
    - Prioritizing Patients in AI: AI healthcare solutions should be developed with a strong emphasis on patient needs and rights, making AI systems user-friendly, accessible, and beneficial to patient health outcomes.
    - Fostering Provider-Centric AI: Patients trust their healthcare providers, hence the efficacy of AI solutions should be viewed through the providers' lens. AI solutions should focus on educating, training, and supporting providers, ensuring a smoother AI adoption journey.
    - Upholding Ethical AI in Healthcare: The four bioethical principles—Beneficence, Non-Maleficence, Justice, and Autonomy—should govern all AI developments in healthcare, asserts Dr. Sriram Rajagopalan. 
    - Promoting AI Accountability in Healthcare: Trust in healthcare AI systems stems from designing them with accountability at the core. These systems should be capable of identifying errors and implementing timely corrections.

3. Securing Health Data and Ensuring AI Transparency:
    - Safeguarding Health Data in AI: As AI's role in managing health data expands, regular security audits can enhance patients' trust in the protection of their health data.
    - Championing AI Transparency: Transparency in AI development fosters trust among users and stakeholders. Information disclosure about AI decision-making models, data sources, and security measures paves the way for ethical AI use in healthcare.

4. Driving Healthcare AI Policies and Global Cooperation:
    - Developing Global Healthcare AI Standards: Collaboration across borders can lead to robust, universally accepted ethical guidelines for AI in healthcare. 
    - Pioneering AI Legislation in Healthcare: Governments should take the lead in designing legislation and regulatory frameworks that balance AI's risks and benefits in healthcare, fostering an environment of innovation.

5. Tackling Bias in Healthcare AI:
    - Eradicating AI Bias: AI systems in healthcare should undergo stringent testing to detect and eliminate biases. A commitment to fairness ensures equal treatment for all patients and fosters trust in AI-driven medical solutions. Diversity within AI development teams is pivotal to challenge bias and bring varied perspectives.


 

RECORDING:


 

PRESENTERS:

Sriram Rajagopalan is a project management guru and Enterprise Agile Evangelist at Inflectra Corporation. Dr. Rajagopalan has wide-ranging and extensive software development and project management experience in many industries. He won prestigious recognition from PMI with the Eric Jennet project management excellence award in 2017. He holds a BE in Electronics and Communication Engineering from the University of Madras in India, an MS in Computer Engineering from Wayne State University, and an MBA in Management from Concordia University. His Ph.D. was in Organization and Management from Capella University. Dr. Rajagopalan possesses many professional certifications in PfMP, PgMP, PMP, PMI-ACP, PMI-SP, PMI-RMP, CSP, CSPO, CSD, CSM, ACC, IT Project+, Six Sigma, SCM, SCPO, SCD, SAMC, SCT, and CSOXP.

Ian Frazier is the Cybersecurity & IT Engineer at Inflectra. Within Inflectra, Ian secures the integrity and stability of the company’s information infrastructure and products. He graduated from the University of Maryland with a master’s degree in Cybersecurity Technology and has completed multiple national certifications specializing in IT security and ethical hacking. He regularly researches security trends and attends DefCon yearly to stay on top of the ever-shifting global security threat landscape. 

 


WANT TO ATTEND OUR NEXT WEBINAR?

Mark your calendars for more events planned in our Influence of AI and ML Technologies - Expert Panel Series. You can also sign up for our monthly newsletter to stay up-to-date with all things Inflectra!

#teamInflectra

Spira Helps You Deliver Quality Software, Faster and with Lower Risk.

Get Started with Spira for Free

And if you have any questions, please email or call us at +1 (202) 558-6885

Free Trial