The Role of Artificial Intelligence in Healthcare
Artificial intelligence is progressively becoming critical to healthcare. It’s being used to improve the speed and accuracy of diagnosis, assist in clinical care, healthcare research and drug development. Artificial intelligence, machine learning and big data profoundly impacted public health interventions, disease surveillance, outbreak response, drug discovery and health systems management in the wake of COVID-19.
AI is also empowering consumers to take greater control of their healthcare and realize their evolving needs. Further, AI is having a significant impact in underserved communities, where telehealth is bridging the gap in access to healthcare.
Dr. Tedros Adhanom Ghebreyesus, WHO Director-General, says, “Artificial intelligence holds enormous potential for improving the health of millions of people around the world.”
Investors certainly understand that. In Q1 of 2021, healthcare AI companies raked in a record-breaking $2.5 billion in 111 deals. This number is up 140% compared to the $1 billion raised in the first quarter of 2020, with the upward trajectory expected to continue.
The State of Artificial Intelligence and Machine Learning in Mobile Health (mHealth):
AI and ML are bringing significant market growth to healthcare. The AI-led health tech market is predicted to reach 120.2 billion by 2028 and is expected to expand at a CAGR of 41.8%.
Top Applications of AI and ML in Healthcare
According to Accenture research, the top applications for artificial intelligence and machine learning include:
- Robot-assisted surgery
- Virtual nursing assistants
- Administrative workflow assistance
- Fraud detection
- Dosage error reduction
- Connected machines
- Clinical trial participant identifier
- Preliminary diagnosis
- Automated image diagnosis
AI and the Future of Transportation
The innovations that artificial intelligence is fueling in urban solutions can bring about multiple benefits like efficient energy, water and waste management, reduction in pollution, noise and traffic congestions and improve the wellbeing and quality of life of people everywhere.
Urban transportation, for example, is one of the biggest polluters. Additionally, it poses a threat to security — 1.3 million people are killed due to road traffic accidents each year, and 93% of these accidents are related to driving errors. Further, urban transport is not inclusive or equally available to all residents.
AI-powered solutions like optimized traffic routing, new modes of transport and autonomous vehicles can significantly cut down emissions, improve safety and make urban mobility more inclusive.
According to Heikki Ailisto, Research Professor at VTT Technical Research Centre of Finland and the Lead of Finnish Center for Artificial Intelligence, “sustainability is a phenomenon whose different aspects are complex, and their interplay makes it even more complicated. It is hard to make mathematical, systemic, or societal models that consider all relevant variables simultaneously. AI, however, can do that. It has been successfully used to optimize, simulate, and control similar complex settings, for example, in the energy sector and medical industry.”
AI Applications in Smart Cities and Urban Mobility
Smart cities and their related activities have always produced data that have informed the insights of local authorities and other stakeholders about the dynamics of those cities, but within a narrow scope. AI can take both data utilization and data-driven decision-making to the next level.
The EU Parliament defines urban AI as “Artifacts operating in cities, which are capable of acquiring and making sense of information on the surrounding urban environment, eventually using the acquired knowledge to act rationally according to predefined goals, in complex urban situations when some information might be missing or incomplete.”
By 2025, AI is expected to power over 30% of smart city applications. These applications encompass solutions that can contribute to urban resilience, sustainability, social welfare and wellbeing of urban residents.
AI applications are evident in every level of the smart mobility and smart city tech stack, including:
Vehicle fleets (autonomous vehicles, electric vehicles)
EV charging stations and plugs (batteries and alternative fuels)
Real estate, parking and services
Electricity grids (wires)
Telecom infrastructure (pipes)
Manufacturing infrastructure (tools)
Beyond these key levels, AI is also responsible for innovations in data and connectivity, data sharing platforms and cybersecurity — all of which work in tandem to shape the future of urban mobility.
AI applications in smart cities and smart mobility can be categorized into:
AI for governance
Urban planning, tailored subsidy provision, disaster prevention and management
AI for living and liveability, safety, security and healthcare
Smart policing, personalized healthcare, noise management and improved cybersecurity
AI for education and citizen participation
Locally accurate, validated and actionable knowledge that support decision-making
AI for economy
Resource (cost and time) efficiency and improved competitiveness through sharing services, efficient supply chains and tailored solutions for customer
AI for mobility and logistics
Autonomous and sustainable mobility, smart routing and parking assistance, supply chain resiliency and traffic management
AI for infrastructure
Optimized infrastructure deployment, use and maintenance of waste and water management, transportation, energy grids and urban lighting
AI for the environment
Biodiversity preservation, urban farming and air quality management
Growing Investments in Smart Mobility
The most significant investments in smart mobility have been related to AI-based solutions and services, including automation, connectivity and electrification.
According to McKinsey, since 2010, investors have poured nearly $330 billion into more than 2,000 mobility companies focused on automation, connectivity, electrification and smart mobility. About two-thirds of the total investment — $206 billion — went to autonomous-vehicle (AV) technologies and smart mobility.
The study also showed that about 90% of these investments went to new entrants in future mobility, with 65% of the investments coming from venture-capital and private-equity companies and 28% from tech companies. Traditional automotive firms accounted for only 7% of the total invested, roughly 20 billion.
AI systems in cities will increasingly work in open, dynamic and hyper-connected environments that will require close collaboration between the private and public sectors. As investments in urban mobility increase, the sector needs new solutions that can help achieve targets like sustainable and equitable mobility and a higher quality of life for residents.
The visionary behind the concept of mobility as a service and CEO of MaaS Global, Sampo Hietanen, says, “Technological development based on AI is not enough unless we have a service that can be sold.”
Juha Salmelin, lead of LuxTurrim5G at Nokia, says, “The technology is ready, but innovations are needed to utilize it for new digital services.”