Conversational AI in low income & resource settings | IGF 2023

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Generative AI and AI technologies have the potential to revolutionise the provision of medical care by overcoming the limitations of time and location, extending healthcare access to a larger number of people, irrespective of their physical location. The use of generative probabilistic models in combination with rule-based care plays a crucial role in bridging the gap between scientific treatments and patients’ understanding.

Addressing healthcare inequity requires collaboration and the appropriate use of technology.

Inequities exist not only among patients but also among countries, states, and healthcare organisations. Through collaborative efforts and leveraging technology, healthcare can be democratised, ensuring equal access to quality care for everyone.

AI technologies can bridge the digital divide in healthcare.

Existing care solutions have the potential to become global solutions if properly validated. Humans play a vital role as transformation agents in bridging this gap, working collectively across silos to ensure inclusivity in healthcare.

Prominent figure Ashish Atreja advocates for a global thought leadership group on generative AI in healthcare.

He believes in the power of collective work and engaging with global partners to drive advancements in healthcare systems. Collaborating and sharing knowledge can contribute to the development and implementation of generative AI solutions worldwide.

Conversational AI has the potential to dispel healthcare fallacies by providing accurate and reliable information.

However, it is crucial that the technology behind conversational AI is based on validated and trustworthy sources. The FDA has a tiered system for validating health-related technologies based on their potential risk, ensuring their reliability and safety.

To ensure the accuracy and effectiveness of conversational AI in healthcare, an automated or semi-automated governance framework is needed.

Currently, there is no specific framework to regulate the validation of conversational AI in healthcare. Establishing such a framework would help maintain the accuracy and credibility of conversational AI, benefiting patients and healthcare providers.

In conclusion, generative AI and AI technologies have the potential to revolutionise healthcare provision, extending care to more people while overcoming limitations of time and location.

Collaboration, inclusivity, and validation of technologies are crucial in addressing healthcare inequity and bridging the digital divide. Through collective work, the creation of a global thought leadership group, and the implementation of an effective governance framework, the potential of AI in healthcare can be fully realised, improving outcomes for patients worldwide.

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In this analysis, several key points and arguments about AI applications in healthcare, the potential of AI and chatbots in low-resource settings, the concept of trust in AI and digital technologies, and the need to establish frameworks for evaluating the reliability and trustworthiness of AI solutions are discussed.

Firstly, the importance of user identification in AI applications in healthcare is emphasised.

The use of facial recognition for digital identity is highlighted as an effective solution implemented for the United Nations Pension Fund. This demonstrates how advanced technologies like AI can be utilised to enhance security and streamline processes within healthcare systems.

Additionally, the potential of AI and chatbots in low-resource settings is acknowledged.

The analysis suggests that these technologies have the ability to address resource limitations and reduce inequalities in healthcare access. To support this argument, a blockchain solution designed and implemented for the United Nations Pension Fund is mentioned. The use of blockchain technology can provide secure and transparent data management, enabling efficient delivery of healthcare services in low-resource settings.

The concept of trust is recognised as crucial in AI and digital technologies.

It is argued that the public should have confidence in the solutions and entities that offer these technologies. The analysis highlights the importance of not burdening individuals with technological details, but rather fostering trust in the overall solution. Trust is seen as a vital factor in promoting widespread adoption and acceptance of AI and digital technologies.

Furthermore, the need to establish frameworks for evaluating the reliability and trustworthiness of AI solutions is emphasised.

The analysis suggests that not all solutions have the same level of reliability, and there is a need to develop criteria for comparing and contrasting different AI solutions. This would enable the identification of trustworthy and reliable solutions that can be implemented effectively.

The speaker believes that such frameworks will promote accountability and transparency in the AI industry.

In conclusion, this analysis brings attention to various critical aspects of AI applications in healthcare, the potential of AI and chatbots in low-resource settings, the concept of trust in AI and digital technologies, and the need for frameworks to evaluate the reliability and trustworthiness of AI solutions.

It underscores the importance of user identification, the potential of advanced technologies in addressing resource limitations, and the value of trust in fostering widespread adoption. Furthermore, it highlights the necessity of establishing criteria for evaluating and selecting reliable AI solutions, promoting accountability and transparency in the industry.

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Conversational AI has the potential to revolutionize the healthcare industry by analysing health conversations and generating valuable insights and decisions. This presents an incredible opportunity to gather and analyze health data from billions of people and clinicians, leading to more effective healthcare outcomes.

Supporters argue that Conversational AI can be the starting point for generating health AI. By leveraging the power of Conversational AI, healthcare professionals can better understand patient needs and tailor treatment plans accordingly.

Conversational AI also addresses the lack of access to basic health information, particularly in rural areas.

Many people living in remote or underserved locations struggle to access crucial information about their health. Conversational AI can bridge this gap by providing easy-to-understand and readily accessible information. Advocates argue that generative AI could eliminate the need for doctors to address basic health problems.

The potential of implementing Conversational AI and generative health AI is widely recognised.

However, no supporting facts are provided to elaborate on this stance.

Conversational AI is also seen as a powerful tool in patient engagement and health-related education. The effort required in typing and texting often hinders effective communication between healthcare providers and patients.

However, Conversational AI streamlines this process by allowing patients to converse naturally, making them feel heard and fostering a better doctor-patient relationship.

Advocates propose the creation of a global generative health AI group under the stewardship of Dr.

Gupta. This group would bring together stakeholders, regulators, policymakers, doctors, hospitals, and frontline health workers to set a direction for all involved. This initiative is supported by the belief that the United Nations, as the largest multi-stakeholder and multilateral body, is in a prime position to facilitate this collaboration.

This would promote partnerships and support SDG3 (Good Health and Well-being) and SDG17 (Partnerships for the Goals).

The Academy of Digital Health Sciences is working on a report about generative health intelligence. This report aims to explore the role of generative health intelligence in shaping the future of healthcare.

While further details about the report’s content or expected release date are not provided, it is expected to contribute to advancements in healthcare intelligence.

Training and deployment of generative AI in healthcare are emphasized as crucial. Understanding how generative AI works and developing the necessary skills are essential for effectively utilizing this technology.

The positive sentiment towards this necessity stems from recognizing the potential benefits of generative AI in improving healthcare outcomes. However, no specific evidence is provided to further support this argument.

In conclusion, Conversational AI has the potential to transform healthcare by analyzing health conversations, delivering information in remote areas, enhancing patient engagement, and facilitating health-related education.

The establishment of a global generative health AI group, the training and deployment of generative AI, and the ongoing work by the Academy of Digital Health Sciences highlight the need to fully harness the potential of this technology. Further supporting evidence and details would strengthen the arguments presented.

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Digital patient engagement is crucial for maintaining relationships with patients even after they leave the hospital. Platforms like WhatsApp play a vital role in this aspect. WhatsApp is a powerful digital tool that enables ongoing interaction between healthcare providers and patients.

It allows doctors, nurses, dieticians, and social workers to provide guidance and answer patient questions. This continuous engagement helps prevent relapses and educates patients about their health conditions. WhatsApp also serves as a platform for passing on education and notices, and as a support system for patients to share ideas and support each other.

However, there are some limitations with the WhatsApp platform, such as delays in response and lack of personalization. Implementing AI in healthcare communication, specifically conversational AI, could address these issues and provide real-time, appropriate responses. Collaboration and knowledge-sharing are essential for driving innovation in healthcare, particularly as technology continues to advance.

By working together, we can improve digital patient engagement and achieve better healthcare outcomes.

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Conversational AI is emerging as a promising solution to improve accessible healthcare in low-income and low-resource settings. A study showed that Conversational AI scored 81% in the MRCGP, surpassing human physicians who scored 72%. This highlights the potential of AI to enhance healthcare delivery and bridge gaps caused by the lack of qualified doctors and inadequate healthcare infrastructure.

AI in healthcare is aligned with SDG 3 (Good Health and Well-being) and SDG 9 (Industry, Innovation, and Infrastructure).

However, there are concerns about awareness and implementation of Conversational AI in low-resource settings. Some digital health professionals are unfamiliar with its concept and potential applications.

This lack of awareness might hinder successful implementation.

Rajendra Pratap Gupta supports using voice-based data through Conversational AI to increase the accuracy and volume of health data, leading to improved healthcare outcomes. Collaboration and a user-centric approach are crucial in AI implementation.

Involvement of different sectors, including the private sector, is vital for sustainable business models. The WHO, ITU, and WIPO play significant roles in facilitating AI implementation.

Addressing the digital divide is important, as 2.6 billion people globally lack reliable internet access, hindering effective AI implementation.

Efforts should be made to increase internet access in underserved areas.

Education in AI and robotics is necessary, with initiatives in place to develop courses for students and train frontline health workers. This will create a skilled workforce to utilize AI technologies effectively.

The debate on regulation in AI continues, with some advocating for guidelines over over-regulation to maintain flexibility and ethical standards while promoting innovation.

In conclusion, Conversational AI shows great potential in improving accessible healthcare in low-income and low-resource settings.

It requires awareness, collaboration, and efforts to address the digital divide and provide education in AI and robotics. Finding the right balance between regulation and innovation is crucial. By addressing these issues, AI can play a significant role in advancing healthcare and achieving the Sustainable Development Goals.

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Artificial intelligence (AI) is widely recognised as a powerful tool that can replace certain skills, while still acknowledging the importance of human involvement. It is acknowledged that AI can outperform humans in certain tasks, offering greater efficiency and accuracy. Notably, humans.ai, led by the CEO and Founder, has achieved significant milestones in AI development, including creating the first AI counselor for a government and an AI capable of real-time conversations with 19 million Romanians.

These accomplishments demonstrate the transformative potential of AI across various domains.

Data traceability and ethics are emphasised as critical considerations in AI development. The CEO’s firm has developed the first blockchain of artificial intelligence to ensure transparency and accountability in AI systems.

Additionally, they have contributed to research papers on the ethical implications of AI, emphasising the need to address these concerns.

In the context of healthcare, the CEO argues for a bidirectional approach to AI, aiming to understand people’s problems and provide effective solutions.

Emphasising human-like interaction, the CEO advocates for grasping individuals’ problems and urgency. They envision an open innovation platform that fosters collaboration and comprehensive problem-solving.

While technology itself is not the issue, optimising its usage is crucial. The CEO suggests that resources for experimenting with AI projects are readily available to everyone.

The focus should be on tackling real-world challenges and driving innovation across sectors.

Furthermore, the CEO asserts that trust can be bolstered in healthcare through the implementation of AI solutions. For instance, the CEO references a project where they cloned a doctor’s voice to send audio messages to patients, enhancing patient care and building trust.

To better understand and regulate AI, the CEO proposes real-world experimentation.

By implementing AI solutions in specific regions, regulators can gain insights and make informed decisions on regulations and policies.

The urgency for action and application of AI is evident throughout the discussion. The CEO highlights the readiness of technology and the availability of skilled professionals passionate about AI.

Encouraging seizing the opportunities presented by AI rather than merely contemplating its potential is emphasised.

In the conversational AI domain, the CEO suggests making the technology more accessible to underserved populations in low-income areas. By developing efficient models that can run on mobile phones, conversational AI can bridge gaps in healthcare access.

Finally, AI is portrayed as a beneficial tool for employment, increasing productivity and reducing human error.

The CEO suggests that AI can supervise performance and mitigate errors, potentially enabling employees to work fewer days while achieving greater results.

In conclusion, AI is a powerful tool capable of replacing certain skills but not humans. The CEO and their firm exemplify the transformative potential of AI across various domains.

Ethical considerations, data traceability, bidirectional approaches in healthcare, effective technology utilization, trust-building, real-world experimentation, accessibility, and increased productivity are crucial aspects guiding the application and development of AI. The overall sentiment strongly favours embracing AI to drive positive change in multiple sectors.

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In this analysis, the speakers focus on the transformative potential of technology, specifically conversational artificial intelligence (AI), in addressing existing gaps in healthcare services. They assert that these gaps, particularly in low middle-income settings, can be effectively tackled through the implementation of technology.

The argument put forward is that technology, especially conversational AI, serves as an enabler in bridging the healthcare divide.

One important observation made by the speakers is the need for a people-focused, collaborative, equitable, and sustainable approach when integrating technology in healthcare.

They emphasize the importance of considering the specific needs of individuals and communities, as well as fostering collaboration between various stakeholders. In addition, they stress the importance of ensuring that the benefits of technology are accessible to all, regardless of socioeconomic status.

The World Health Organization (WHO) plays a crucial role in this conversation by providing guidance and support for the effective implementation of AI in healthcare.

The speakers highlight WHO’s efforts in maximizing the value of AI in healthcare through initiatives such as the global collaboration with the International Telecommunication Union (ITU) and the World Intellectual Property Organization. These efforts aim to harness the potential of AI to improve global health outcomes.

Ethics and regulations emerge as important considerations in the implementation of AI in healthcare.

The speakers stress the need for ethical approaches to AI development and deployment, ensuring that the technology is used in a responsible and beneficial manner. They also highlight the importance of regulations to provide guardrails and prevent potential misuse of AI.

However, it is asserted that regulations should not stifle innovation but instead strike a balance between regulation and technological advancement.

Education and training play a significant role in achieving responsible AI implementation. The WHO offers courses on ethics and governance of AI to promote understanding and ethical approaches among developers, policymakers, and implementers.

These courses aim to equip individuals with the necessary knowledge and skills to navigate the complex ethical considerations surrounding AI implementation.

In conclusion, the analysis underscores the potential of conversational AI in addressing healthcare gaps and improving global health outcomes.

A people-focused, collaborative, equitable, and sustainable approach is deemed essential in effectively implementing technology in healthcare. The WHO’s guidance and support, along with the development of educational courses, ensure that AI is deployed ethically and responsibly. It is evident that harnessing the potential of AI requires a well-balanced approach that brings together technology, ethics, regulations, and education for the betterment of healthcare systems worldwide.

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During the discussion, the potential of conversational AI to bridge the healthcare gap was highlighted as a significant advantage. The ability of AI to provide 24/7 assistance and access to healthcare globally, through mobile phones, was emphasized. This can greatly benefit individuals in remote areas or those who may have limited access to healthcare services.

The convenience and availability of AI-based healthcare assistance can help address health disparities and provide support to individuals in need.

The combination of AI with blockchain technology was also discussed as an efficient solution during crisis situations. It was mentioned that during the COVID-19 pandemic, an AI chatbot combined with blockchain technology helped locate over 10 billion pieces of personal protective equipment (PPE) within the first 24 hours.

This demonstrates the potential of AI and blockchain to rapidly respond to critical needs and find effective solutions in times of crisis.

The importance of fact-checking AI and ensuring its accuracy was emphasized. Even though AI is probabilistic and not always correct, it is crucial to verify the information provided by AI systems.

One of the speakers, the president of Guardrail Technologies, highlighted the need to put guardrails around AI and fact-check generative AI to ensure its reliability and accuracy. This point stresses the importance of being cautious and critical when relying on AI-generated information.

The discussion also raised awareness about the issue of internet access and connectivity for AI solutions to be effective.

It was mentioned that 2.6 billion people globally lack internet access, which significantly hinders the overall success and reach of AI solutions like chatbots. Ensuring internet access for all individuals, especially those who currently lack it, is necessary to fully harness the benefits of AI and provide equitable access to its solutions.

A holistic approach that considers individual needs, even in remote locations, was emphasized.

The experience from an IBM Watson project was shared, where access points were set up in various villages, allowing people to reach these points in half a day and gain access to medical information. This approach recognizes the importance of tailoring AI solutions to meet the specific needs of individuals regardless of their location or resources.

Lastly, the speakers acknowledged the complexity of implementing AI solutions on a wide scale.

It was acknowledged that the challenge extends beyond just conversational AI and that the complexity of the problem makes it difficult to implement AI solutions effectively. This realistic perspective highlights the need for careful planning, research, and collaboration to overcome these implementation challenges.

In conclusion, the potential benefits of conversational AI in bridging the healthcare gap, providing 24/7 assistance, and access to healthcare globally through mobile phones were discussed.

The combination of AI with blockchain technology was seen as an efficient solution during crisis situations. The importance of fact-checking AI and ensuring its accuracy, considering internet access and connectivity, adopting a holistic approach, and addressing the challenges of implementing AI solutions were all key points discussed during the session.

Overall, the speakers expressed optimism about the potential of AI while also acknowledging the complexities and challenges that need to be addressed for its successful integration.