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- 🌞 Microsoft's Digital Pathology Model
🌞 Microsoft's Digital Pathology Model
Plus: Epic releases open-source AI validation
Welcome to your briefing:
AI ROUNDUP: Microsoft unveils new foundation model for digital pathology in clinical medicine
INDUSTRY ROUNDUP: Mayo Clinic taps Zipline for drone delivery
WELLNESS BYTES: The 2 best exercises for lower blood pressure
INSIGHTS CORNER: Navigating the ethical landscape of Generative AI
TRIVIA: What groundbreaking feat did Insilico Medicine achieve in 2022 to accelerate drug discovery?
AI ROUNDUP
WATCH THIS - How GE HealthCare plans to build AI from India for the world
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Epic releases open-source AI validation tool for health systems (Read More)
AI Model fails to predict penicillin allergy although key drivers identified (Read More)
Satya Nadella, CEO Microsoft on “The age of AI transformation” (Read More)
5 factors to consider when validating radiology AI (Read More)
85% of Neuralink implant wires are already detached, says patient (Read More)
Twin health announces Digital Twin AI for weight loss with GLP-1 elimination (Read More)
Microsoft unveils new foundation model for digital pathology in clinical medicine (Read More)
Fortune/PINC AI 15 Top Health Systems 2024 (Read More)
INDUSTRY ROUNDUP
Oracle’s Cerner unit customer losses to Epic accelerated in 2023 (Read More)
SpaceX Starlink launch boost for Indonesia healthcare (Read More)
HHS “Letter to Health Care Leaders on Cyberattack on Change Healthcare” (Read More)
Biopharma layoff tracker 2024: Evotec, Lyra, Takeda and More Cut Staff (Read More)
Mayo Clinic taps Zipline for drone delivery of meds, supplies to hospital-at-home patients (Read More)
WELLNESS BYTES
INSIGHTS CORNER
Navigating the Ethical Landscape of Generative AI
As generative AI technologies advance rapidly, organizations face complex ethical dilemmas and compliance challenges. From IBM's perspective, it's crucial for leadership at all levels to actively engage in shaping responsible AI practices that align with human values.
Core Ethical Concerns in AI Deployment Organizations must address several critical ethical considerations to responsibly leverage AI technologies:
Data Protection: Safeguarding sensitive information is paramount to prevent misuse and ensure privacy.
Intellectual Property: Respecting copyrights and ensuring AI does not infringe on the rights of others.
Bias and Accuracy: Identifying and mitigating biases in AI algorithms to avoid discriminatory outcomes and ensure the accuracy of AI outputs.
Strategies for Ethical AI Implementation To effectively manage these ethical challenges, organizations should adopt a comprehensive approach:
Transparency and Accountability: Develop clear policies that outline the use and limitations of AI technologies, ensuring stakeholders understand how AI applications function and the origins of the data used.
Ethical AI Culture: Foster an organizational culture that prioritizes ethical considerations in AI development, emphasizing human well-being and environmental sustainability.
Ongoing Monitoring and Evaluation: Regularly assess AI systems and their impacts, adapting policies as necessary to align with ethical standards and societal values.
From IBM’s Insights: Critical Actions for Ethical Leadership
Empower Ethics Teams: Ensure that ethics teams are not only part of the discussion but are equipped with the resources to influence meaningful change.
Consumer-Centric Trust: Build and maintain trust by aligning AI practices with consumer expectations, transparently sharing how AI technologies are used and managed.
Preparation for Compliance: Despite regulatory ambiguities, organizations should proactively prepare for compliance by embedding ethical considerations into all AI and data-related investments.
Engaging Broadly for Ethical AI
Stakeholder Engagement: Collaborate with a wide range of stakeholders, including privacy officers and compliance teams, to foster comprehensive AI governance.
Balancing Automation and Human Oversight: Create synergies between automated systems and human decision-making to ensure AI augments rather than replaces human capabilities.
Aligning Partnerships: Choose to partner with other organizations, academics, and startups that share a commitment to ethical AI, ensuring that the broader innovation ecosystem reflects shared values.
Building Trust Through Ethical Practices
Consumer Trust: Transparent and responsible AI use is critical for sustaining a positive reputation and consumer trust. Continuous communication and adherence to ethical practices are essential.
Employee Alignment: Employees are more likely to commit to organizations that reflect their values on social responsibility. Promoting an ethical workplace attracts talent and enhances job satisfaction.
Documentation and Regulatory Readiness
Proactive Documentation: Keep detailed records of all AI applications and governance practices to ensure traceability and accountability, which will be vital for compliance as regulations evolve.
Adaptability to Regulatory Changes: Stay informed about global regulatory trends and be ready to adjust practices swiftly to comply with new laws and guidelines.
Conclusion IBM emphasizes that as generative AI reshapes various sectors, the responsibility to implement these technologies ethically cannot be understated. Organizations that prioritize ethical frameworks, stakeholder engagement, and transparent practices will not only navigate the challenges of AI but will also lead in fostering trust and integrity in the digital age.
Access the full report here
AI TRIVIA
What groundbreaking feat did Insilico Medicine achieve in 2022 to accelerate drug discovery? |
HEALTHCARE CONFERENCES
June 5-6: Digital Healthcare Innovation Summit (East Coast - Boston)
June 8-12: American Medical Association Annual Meeting of the House of Delegates (Chicago)
June 11-13: America's Health Insurance Plans AHIP 2024 (Las Vegas)
June 24-27: Healthcare Financial Management Association Annual Conference (Las Vegas)
June 29-July 2: AcademyHealth Annual Research Meeting (Baltimore)
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