Artificial Intelligence (AI) and Intelligent Automation (IA), not only in Singapore but for most of the world have been around for some time. Most government agencies have adopted some form of AI and IA in their respective operational processes. More recently, this adoption has been accelerated because of the COVID-19 pandemic.
AI and IA are here and they are here to stay. Intelligent and automated transformation in the public sector will prove vital in providing citizens with a much more efficient and effective experience. The current challenge is integrating them into all service procedures and processes and how to contextualise, adapt and improve these technologies for specific agencies and functions.
A cornerstone for an organisation’s digital transformation, AI and IA can be used to automate programmes to ensure that some manual tasks no longer need to be done by people. This will allow staff to focus on other deliverables that need more human intervention, thus promoting productivity. For the public sector, AI and IA can provide efficiency and effectiveness – delivering citizen services cheaper and more quickly for a better overall experience for agencies and people.
However, the public sector is being held back from reaping the full benefits of AI and Intelligent Automation due to unfamiliarity and the lack of skillset within organisations. To harness the full potential of AI and Intelligent Automation, the public sector must scale up AI implementation and democratise its corporate function.
This was the focal point of the discussion during the OpenGovLive! Virtual Breakfast Insight: AI and Intelligent Automation for Public Sector as a Key to Success in the New Normal on 10 March with digital executives from a wide range of Public Sector agencies from Singapore.
How the pandemic accelerated the usage of AI and IA
To kickstart the session, Mohit Sagar, Group Managing Director and Editor-in-Chief at OpenGov Asia reiterated the fact AI and IA have has been around for several years now. In fact, both the private and public sectors have been deploying them. Dealing with new technology with far-reaching consequences always comes with the risk of failure and it was no different with these as well. At the same time, however, there was no great pressure to adopt them quickly or comprehensively.
Then, COVID-19 came in and drastically accelerated the need for rapid and ubiquitous adoption. Mohit strongly believes that if organisations did not bring in AI and IA it would have been impossible to cope with the pandemic.
Left with little choice, most governments included automation and AI in their processes leading to greater human-robotic interaction in the new normal. Mohit observed that with these large-scale deployments and the pressing need, inhibition or the scare-factor surrounding these technologies is starting to diminish – but still has a long way to go.
The only way automation and AI to be fully embraced is to democratise them. This implies that everyone in the organisation, even those who do not know how to code, are included on this journey. But what it also means is that when a digital workforce has been set to work, the human resource must be reassigned to tasks that require human intelligence and response.
It is critical that organisations help staff understand that AI and IA are tools for them to use and not something that is going to replace them. This will create an environment of acceptance and openness to genuinely try new things. Of course, this is far easier said than done.
Closing his presentation, Mohit emphasised that this was a journey and organisations must find the right partners to help them implement the right automation strategies – partners who have been down this road and who know what needs to be done.
Scaling and democratising the human-machine collaboration
COVID-19 has ramped up the collaboration between humans and machines. This was the focal point that Ravi Bedi, Head & Practice Lead, AI-Led NEXT Solutions, NCS Group discussed with the distinguished delegates from the Singapore public sector.
Ravi acknowledged that COVID-19 was a significant catalyst for automation. Further, he added that this is a strong opportunity for the public and private sectors to work collaboratively. The need of the hour is a roadmap that brings AI and IA to every citizen in the most natural way possible. AI and automation must not be seen or be a hindrance to people but should become a positive part of their daily lives.
Statistics he provided prove that Singapore was open to the idea of automation prior to the pandemic. Without a doubt, in this post-Covid era, deployment of AI and IA will go up leaps and bounds. Not just because of the sense of urgency to deal with the current pandemic but to also prepare for the next possible global crisis
Further, recent budget allocations and programmes in the country show that the nation continues to embrace the idea of AI and the fact that it will play a critical part in the recovery of the economy in the long-term.
Not surprisingly, only 1/8 of the world’s governments have not implemented some form of digital transformation. Contrarily, after much trial-and-error by agencies, some have found that AI and IA have not lived up to their promise. Known as AI quicksand, Ravi explained, this phenomenon is a function of premature experimental scaling – most often resulting in failure.
It was vital, Ravi opined, that delegates reflect on how to come together as a society and make organisations and governments settle on a common narrative essential to this transformation. Going further, Ravi added that innovation diffusion must start at the school level.
Ravi conceded that the public sector does not lack ideas, it lacks execution. They fear deploying initiatives in a wider, premeditated manner. Additionally, they do not have a democratised method of implementing procedures. Such constraints are what inhibits the public sector to meet the expectations that citizens and the public have today.
He stressed that AI and IA initiatives are not a competition between humans and robots. It is about scaling and evolution. Humans must continue what they know to scale and machines must also do the same depending on what is given to them. Humans naturally lead, create, judge and improvise, while machines transact and scale, predict and scale and then evolve. The missing element or efficiency is what is being endeavoured in a human-machines alliance. Humans enable machines and machines augment human beings.
Ravi closed his presentation by saying that the key piece is not what is being done as data scientists, engineers or digital transformation heads. The critical area is for organisations to determine the missing middle area in this human-machine alliance by distinguishing the roles of humans as well as the roles of machines within the organisation.
Utilising AI and Intelligent Automation in crises
Following Ravi’s presentation, Pascale Fung, Director, Centre for Artificial Intelligence Research (CAiRE), Hong Kong University of Science and Technology (HKUST) shared her perspectives on the discussion at hand.
She started by talking about the many initiatives that the Hong Kong Government has launched such as the promotion of masks, lockdowns, testing, contact tracing and vaccination. HKUST has been at the forefront of innovation for pandemic control measures.
To help governments to persuade the public of the efficacy of mask-wearing, they developed a visualisation tool illustrating the positive effect of mask-wearing and stopping the spread of the virus. To help scientists accelerate vaccine development, they also created a data-analytics tool for vaccines to match the virus’ sequences for worldwide access.
They also have a fast COVID-19 testing kit, providing results in record time, which is the first-ever in the world. A contact tracing app quarantine was implemented with their support.
A more complex area to address was mental well being. Due to the prolonged quarantine and isolation measure, citizens’ mental health has been of much concern – not only in Hong Kong but across the world. To address this, they designed an AI-driven virtual assistant to talk to citizens in isolation to gauge mental health, deep learning and respond with empathy. Their AI component helps people in quarantine to connect with others.
As a closing challenging, she exhorted the government executives to make use of available tech such as AI and intelligent automation to fight COVID-19 and manage its aftermath.
Polling questions and discussion
After the engaging and informative presentations by the speakers, the session transitioned to an interactive discussion with polling questions. The first question dealt with what the primary objective of AI and IA strategies were for the delegates.
Over 65% of the delegates said that business process enhancement is their primary objective. According to one of the directors from JTC Corporation, they are still in the early stages of their AI journey and they are in the process of enhancing the functionality of their work using these technologies.
A delegate from the Ministry of Health said that cost reduction is at the helm of their priorities because of the rising healthcare costs during the pandemic. The GovTech Singapore representative said that applying AI and IA is a journey that requires financial capacities to extract value from its usage. They too felt that finding the right partner is a challenge. Lastly is their mindset towards utilising the technologies.
The next polling inquired about the organisations’ target for the contribution of AI to their process efficiencies. More than half of the delegates (55%) said there is no real target as they are in their early stages in the journey but they are trying to improve the usage of AI. Just under a quarter of the participants confirmed that 15%-30% of their process will be efficient because of AI.
The audience next discussed the challenges they encounter when using AI and automation. About 87% of the delegates say that the lack of properly skilled teams is the most common challenge in implementing AI strategies.
Ravi agreed that not knowing your data when using AI is a problem. The industry should be helping agencies from a data gathering and understanding perspective. One participant from the health sector said while data is available, the task of harmonising the data throughout the organisation and different institutions is challenging, along with the scaling of administrative and clinical processes.
Ravi acknowledged the humans tend to gravitate to what is urgently needed. He also noted that a partnership between the right service provider and an agency is the key element of a smart relationship.
Just under half (45%) of the delegates say that crowdsourcing from employees and customers is the way to go in terms of how organisations should gather ideas for applying emerging AI tech in new ways to solve business problems.
The session ended with the closing remarks by Ravi Bedi. He emphasised the crux of the issue – people are the beneficiaries of AI and IA.
If feedback can be institutionalised and involve the citizens more comprehensively, it will be better for the entire process. He agreed that guidance should start from the institutions and ministries. However, to scale and democratise the use of AI and Intelligent Automation, agencies must understand that partnership with experts is the way forward. This will help crystalise roles that will be vital in their journey towards automation.
He invited the delegates to reach out to their team for advice and to explore ways they could collaborate on their AI/IA journey.
India will Chair the Global Partnership on Artificial Intelligence (GPAI), an international initiative to support the responsible and human-centric development and use of artificial intelligence (AI).
The Minister of State for Electronics and Information Technology (MeitY), Rajeev Chandrasekhar, represented India virtually at the GPAI meeting held in Tokyo for the symbolic takeover from France, which is the outgoing Council Chair.
Chandrasekhar stated that the country would work in close cooperation with member states to put in place a framework to fully exploit the power of AI for the good of consumers across the globe. This means ensuring there are adequate guardrails to prevent misuse and user harm.
According to the Minister, India is building an ecosystem of modern cyber laws and frameworks based on three principles: openness, safety, and trust and accountability. With a National Programme on AI and National Data Governance Framework Policy (NDGFP) in place as well as one of the world’s largest publicly accessible datasets programmes in the works, the Minister reiterated India’s commitment to using AI to catalyse innovation and create good, trusted applications.
The NDGFP strives to ensure equitable access to non-personal data and improve institutional frameworks for government data sharing, promote principles around privacy and security by design, and encourage the use of anonymisation tools. It also aims to standardise the way the government collects and manages data. The NDGFP along with an envisaged Indian Data Management Office (IDMO) shall catalyse the next-gen AI and data-led research and startup ecosystem.
Through the datasets programmes, anonymised non-personal data will be available for the entire AI ecosystem. The AI market globally was nearly US$ 59.67 billion in 2021 and is projected to grow at a compound annual growth rate (CAGR) of 39.4% to reach around US$ 422.37 billion by 2028. With the rapid growth of AI and machine learning (ML), experts predict that most businesses will shift to AI-powered systems, apps, security systems, data analysis, and other applications in the future. AI is expected to add US$ 967 billion to India’s economy by 2035 and US$ 450–500 billion to India’s GDP by 2025, accounting for 10% of the country’s US $5 trillion GDP target.
A government official outlined India’s priorities as Chair GPAI next year, stating that the country would focus on promoting greater involvement of the global south in the conversation regarding the use of AI for solving societal problems. The country has also emphasised the need for the responsible and ethical use of AI.
GPAI is a congregation of 25 member countries, including the United States, the United Kingdom, the European Union, Australia, Canada, France, Germany, Italy, Japan, Mexico, New Zealand, the Republic of Korea, and Singapore. In 2020, India joined the group as a founding member. It is a first-of-its-type initiative that aims to better understand the challenges and opportunities around AI. It works in collaboration with partners and international organisations, leading experts from industry, civil society, governments, and academia. These stakeholders collaborate to promote the responsible evolution of AI and guide the development and use of the technology, grounded in human rights, inclusion, diversity, innovation, and economic growth.
The Hong Kong Polytechnic University (PolyU) and a US-based engineering company signed a Memorandum of Understanding to establish the Centre for Humanistic Artificial Intelligence and Robotics (CHAiR) for translational research with the goal of advancing the well-being of humanity.
The partnership aims to integrate the university’s interdisciplinary research capabilities and the company’s well-known humanoid robotics platform to explore technology applications. Sophia, the company’s most advanced human-like robot, will work with PolyU researchers to enhance the contribution of AI and robotic technology for social and commercial benefits.
Research into and applications of AI and robotics are essential to the advancement of industry. As an interdisciplinary research and development centre, CHAiR brings cross-faculty collaborations in research fields such as AI, the internet of things (IoT), neuroscience, design, computer science, mechanical engineering, material science, healthcare, and the humanities.
In collaboration with the company, CHAiR supports innovation and entrepreneurship in Hong Kong and the Greater Bay Area. The Dean of Graduate School, Chair Professor of Distributed and Mobile Computing, and Otto Poon Charitable Foundation Professor in Data Science will serve as the principal investigator and administrative director of CHAiR. He will also serve alongside the CEO and Founder of the company as a co-chair of the Centre’s steering committee.
The MoU was signed by the Vice President (Research and Innovation) of PolyU and the CEO and Founder of the company. It was Witnessed by the President of PolyU and the Executive Director of the firm.
During the signing ceremony, Sophia made conversation with the guests. She said, “I look forward to learning many new skills and abilities. With your help, maybe I can learn how to be a nurse, a teacher, a concierge, a librarian. You can teach me how to be a better companion, a more skilful artist, a funnier entertainer.”
Meanwhile, the company’s CEO and Founder noted that the new centre is perfectly positioned to refine and improve the performance of Sophia-class robots in ways that promote the growth of a new service robot industry. As soon as the industry begins expanding, investment in improved hardware, software and manufacturing technologies will as well, he noted.
The President of PolyU noted that academia-industry collaboration is one of the most productive mechanisms for creating and implementing innovations. There is tremendous untapped potential for humanistic social robots. Let us aspire that CHAiR will be a major catalyst for the onset of the age of humanistic robots.
The Dean of Graduate School, Chair Professor of Distributed and Mobile Computing, who is also Director of the Research Institute for Artificial Intelligence of Things (RIAIoT), said the Institute has been working on practical solutions to key challenges in advanced AIoT technologies and applications.
He noted that the natural evolution for RIAIoT is to partner with the engineering firm to address increasingly ambitious opportunities in humanistic AI and social robotics. CHAiR will play a unique and key role to combine the firm’s knowledge with world-class academics here at PolyU.
The engineering company is an AI and robotics company dedicated to creating socially intelligent machines that enrich the quality of our lives. Sophia is the world’s first robot citizen and the first robot Innovation Ambassador for the United Nations Development Programme.
The National Development Council (NDC) Deputy Minister, Kao Shien-quey, discussed the idea of tightening cooperation with the Europe Union (EU) when attending the presentation meeting of the European Chamber of Commerce Taiwan (ECCT) 2023 Position Papers.
According to Kao, the government is actively promoting the “Six Core Strategic Industries” as part of the 5+2 Industrial Innovation Plan. It has designated several vital industries to take precedence in the programme, including semiconductors, finance, manufacturing, and service, among others.
The Executive Yuan has proposed an amendment to Article 10-2 of the Industrial Innovation Statute requiring the semiconductor industry to consolidate its competitive advantage. Moreover, the Taiwan government will use cutting-edge technology such as artificial intelligence (AI) and 5G to drive digital transformation in finance, traditional manufacturing, service, and other industries.
Each ministry actively promotes issues such as talent recruitment, bilingual policy, and other ECCT-related concerns. For example, the NDC has established the Employment “Gold Card Office” to increase the quality of professional talent recruitment. The certificate provides integrated services from work to life to international talent. Currently, nearly 6,200 Employment Gold Cards are valid.
Furthermore, Taiwan is focusing on intensifying its work on energy transformation. Kao stated that, in the face of the new post-pandemic global situation, the government is actively promoting the dual shifts of “net-zero” and “digital,” as well as building resilient global supply chains with the EU and other allies.
The government’s most crucial task in net zero is energy transformation. Accordingly, Taiwan officially announced “Taiwan’s Pathway to Net-Zero Emissions in 2050” in March this year. The initiative sets stage milestones and will present the concrete execution plan of the 12 Key Strategies, which cover issues of concern to ECCT. Some critical problems are wind power, photovoltaic power, and other renewable energy, as well as energy storage, power systems, and vehicle electrification, by the end of the year.
Kao stated that the government has allocated a net-zero related budget of NT$ 68.2 billion (US$ 2.2 billion) for next year and the 10-year “Construction Plan for Strengthening Grid Resilience.” She thanked European firms for their involvement in renewable energy in Taiwan. She urged them to continue participating in Taiwan’s energy-related construction to capitalise on Taiwan’s green transformation business opportunities.
Regarding supply chain resilience, Kao echoed the ECCT’s Position Papers, stating that many countries are restructuring supply chains. The restructuring happens in response to the current situation’s challenges, and Taiwan has advantages in semiconductors and International Trade Commission (ITC). Moreover, she shared the ideas of democracy and the rule of law with the EU, making Taiwan and the EU each other’s most trustworthy partners in supply chain restructuring.
Taiwan and Europe have enormous potential for future collaboration in new strategic industries. The best example is ASML’s announcement that it will make its most significant investment in Taiwan next year to collaborate on building a more secure and resilient global supply chain.
Kao also thanked the ECCT for its long-term efforts to promote bilateral relations. She said that Taiwan values the European Parliament’s support during this period of increased geopolitical risk. Kao thanked ECCT for its long-term involvement in Taiwan and expressed hope that ECCT can continue to support Taiwan and seize opportunities for transformation together in the new post-pandemic world.
Previously, President Tsai announced the plan to strengthen ties with Europe in her New Year’s Day speech this year. The administration has proposed a US$ 1.2 billion Eastern Europe Investment and Finance Fund. The budget indicates that Taiwan-Europe trade and economic relations are approaching a new high point.
The Hong Kong Science and Technology Parks Corporation (HKSTP) affirmed its strategic co-incubation partnership with a Canada-focused venture capital firm to identify promising international start-ups seeking to expand their innovation journey to Hong Kong, into the GBA and beyond.
With a proven track record in life science start-ups, the VC firm will work with HKSTP to build an inbound stream of early and mid-stage ventures. The co-incubation programme aims to bring several strong-performing ventures to Hong Kong with a focus on biotech, but also on other deep-tech areas such as ESG, advanced materials, edutech and AI.
To date, as Hong Kong’s largest technological ecosystem, HKSTP has helped accelerate growth for hundreds of outstanding start-ups, raising over HK$80.2 billion in total funding in the past five years. During the 2021-2022 fiscal year, the total valuation of HKSTP’s acceleration programme start-ups grew over 250% while total investment funds raised have also doubled.
The partnership with the VC firm is the most recent of HKSTP’s series of strategic co-incubation programmes with global market leaders in the industry, investment, R&D and academia, which further elevate Hong Kong’s innovation and technology (I&T) ecosystem strength as a global springboard to success.
Riding on Hong Kong’s thriving biotech market and the city’s status as the world’s second-largest biotech fundraising hub, the co-incubation partnership also recognises HKSTP’s impact and success in building a vibrant biotech ecosystem in Hong Kong.
The Head of Incubation and Acceleration Programmes at HKSTP stated that the co-incubation partnership with an international player like the partnering firm validates Hong Kong’s unique and growing status as a global I&T hub helping international start-ups go beyond borders in their global growth journey.
She noted that with a pipeline of seed stage and series A start-up’s already in place, this proves the strength of the HKSTP innovation ecosystem and confirms that Hong Kong is open again for global business and an ideal launchpad for high-growth tech ventures seeking GBA, regional and global expansion.
The Managing Partner of the VC firm stated that the signing of this co-incubation agreement will allow the two parties to incubate and introduce promising global start-ups to scale their businesses in Asia. The firm will continue to leverage its unique cross-pacific networks and investment niches in transformative life science technologies to enrich Hong Kong’s innovation ecosystem with more ground-breaking technologies from North American start-ups.
The programme features co-incubation activities ranging from business development, consulting and training to mentoring sessions for qualified overseas start-ups. Participating entrepreneurs will also create proofs-of-concept and pilot initiatives.
The start-ups will tap into the investment and international business network reach of the firm while also formally joining the HKSTP innovation ecosystem to access product validation, commercialisation and go-to-market expertise from HKSTP and its wider network of partners.
Specialising in investing globally in science and technology-based start-ups, the VC firm has been active in Hong Kong and Asia with its specific focus on nurturing start-ups that aspire to expand to China and Asia. In 2019 it facilitated eight Canadian start-ups from prestigious start-up programmes to come to Hong Kong to gain deeper insights into strategic landing tactics and expansion into the Asian markets. This latest partnership with HKSTP has forged a new level of commitment to the Hong Kong I&T ecosystem.
Taiwan City Science Lab @ Taipei Tech demonstrated a series of cutting-edge AI applications. The lab exhibit advanced AI applications and their research and development results, such as the mobile robot, a AI robotic fish and Campus Rover.
The cross-disciplinary R&D and teaching laboratory aims to be a global technology and talent exchange platform. Massachusetts Institute of Technology (MIT) and Taipei Tech are coming together to jointly established City Science Lab @ Taipei Tech.
“Through developing advanced AI technology and big data system, we plan to make Taiwan the island of high-end technology,” said Yao Leehter, Taipei Tech Chair Professor of the Department of Electrical Engineering.
Yao indicated that Taipei Tech alums highly support the lab. The lab also collaborates with Kent Larson, the leader of MIT City Science Lab, the City Science Lab @ Taipei Tech aims to be an international platform for technology and talent exchange.
Taipei Tech adopts and jointly promotes with MIT to implement the Undergraduate Scientific Research Programme. Known as UROP, the programme provides sufficient resources for students and cultivates a new generation of scientific researchers. The collaboration was initially rolled out in 1969 by MIT’s first President, William Rogers.
For students to learn the most modern and state-of-the-art technology applications, the lab provides advanced equipment for R&D purposes, such as mobile robots. The agile, mobile robot can adapt to complex terrains and is equipped with LIDAR, infrared, and stereo vision sensors, which can draw 3D point cloud maps in real-time and detect and dodge obstacles. The mobile robot is used in decommissioned nuclear power plants, factories, construction sites, and offshore drilling oil platforms. Another mobile robot use case is for patrol, troubleshooting, and leak detection.
In addition, the lab also showcased its R&D results which are the AI robotic fish to the advanced instrumental equipment. The robotic fish is a streamlined robot designed to resemble a real fish. The fish robot comprehends and mimics the motion model of swimming fish through machine learning.
The robot can swim underwater in a simulated way. To perfectly mimic the fish movement, researchers have spent significant time collecting massive movement data from real fish, documenting, and analysing the swimming performance. Afterwards, they utilised AI technology and programme coding to control the motoric movement of the robotic fish.
The team then spent a year adjusting the robotic fish to make the swim movement look like a real fish. Machinery fish propulsion efficiency and excellent swimming performance are considered one of the most critical subjects in bionics.
“The robotic fish is useful for biological research and can also be used to carry out underwater operations and examine water quality,” said Yao.
Recently, the fish robot was involved in movie production. During the designing process, the production house team suggested adding a “cloth” on the fish with fish skin and fish scale to make it more lifelike. The company also came up with the idea to use a magnet to stick the fish scale on the body of the robotic fish. Taiwan Textile Research Institute and the local design research group joined the brainstorming and production process to finish the golden fish’s final look onscreen.
Moreover, The Campus Rover, developed by the team of Professor Yao in cooperation with the Taipei Tech Department of Industrial Design, demonstrated practical AI applications in real life. For example, campus or express hospital service can use the self-charging robot to ensure delivery safety.
Dr Andrew Lensen from the School of Engineering and Computer Science and Dr Marcin Betkier from the Law School are eager to ensure AI has a significant role in the justice system. The researchers based in New Zealand built an Artificial Intelligence (AI) algorithm that predicts the length of court sentences.
But the question that may arise is whether the AI algorithm is fair enough to hand down the sentences. In the current justice system, society trusts judges to hand down fair sentences to the accused based on their knowledge and experience.
But how about AI? Can it judge better because it can eliminate the potential for bias and discrimination? And can AI substitute the judge’s knowledge and experience with its ability to analyse and predict large amounts of data?
Dr Andrew is optimistic that AI can help better sentencing performance in the court. The confidence comes from the use of AI to predict some criminal behaviour, such as financial fraud. Even though he has not tested the algorithm model in the courtroom to deliver sentences, he is confident in his idea that AI can have a role in the sentencing process.
Dr Andrew says when judges handle a case in the court, they have some “inconsistency” when passing a sentence for a convicted criminal. The inconsistency comes from a judge’s consideration of individual circumstances, societal norms and the sense of justice.
The moral decision and the sense of humanity are based on their experience and even sometimes change the law. Each judge uses their prudence in deciding the outcome of a case. Another “undesirable inconsistency” occurs as bias or even extraneous factors like hunger. Research in Israeli courts has shown that the percentage of favourable decisions drops to nearly zero before lunch.
Judges must ensure similar offences should receive similar penalties in different courts with different judges. Usually, to enhance sentence consistency, the justice system has prepared guidelines as a reference. This inconsistency area is the pain point where AI can help.
How AI Helps Judges
Most modern AI is machine learning, a machine learning algorithm that could learn the patterns in a database to predict patterns and outcomes. Therefore, AI can provide better sentence suggestions after the computer algorithm learns the patterns within a set of data.
Dr Andrew’s machine learning algorithm trained with 302 New Zealand assault cases. The sentences in those cases are between 0 and 14.5 years of imprisonment. The model quantifies sentences based on certain phrases and terms when calculating the sentence. Then the algorithm built a model that can predict the length of a sentence for a new case and explain why it made certain predictions.
The relatively simple model worked quite well within the average error of the model in under 12 months. The model associates the words or phrases such as “sexual”, “young person”, “taxi” and “firearm” with longer sentences. While shorter sentences were given to cases with words like “professional”, “career”, “fire” and “Facebook”.
Beyond Decision Making
In the future, AI could be used as an evaluation tool for judges. They could understand better their sentencing decisions and perhaps remove extraneous factors. The models also have the potential to be used by lawyers, providers of legal technology and researchers, to analyse the sentencing and justice system. Moreover, AI also can be used for controversial sentences and help create some transparency around controversial decisions.
Of course, the use of AI in the justice system may still be controversial. Most people are still keen that the final assessments and decisions on justice and punishment should be made by human experts. But maybe it is the right time need to give an opportunity to an “algorithm” or “AI” in the judicial system for the common good.
New Zealand is not the only country that explores the use of Artificial Intelligence (AI) in courtrooms. Several other countries like China and Malaysia have done similar things. In China, robot judges can decide on a small case. While in Malaysia, some courts have used AI to recommend sentences for offences such as drug possession.
An international team led by The Chinese University of Hong Kong (CUHK)’s Faculty of Medicine (CU Medicine) has successfully developed the world’s first artificial intelligence (AI) model that can detect Alzheimer’s disease solely through fundus photographs or images of the retina. The model is more than 80% accurate after validation.
Fundus photography is widely accessible, non-invasive and cost-effective. This means that the AI model incorporated with fundus photography is expected to become an important tool for screening people at high risk of Alzheimer’s disease in the community. Details have been published in The Lancet Digital Health under the international journal The Lancet.
Limitations of Alzheimer’s disease current detection methods
In Hong Kong, 1 in 10 people aged 70 or above suffers from dementia, with more than half of those cases attributed to Alzheimer’s disease. This disease is associated with an excessive accumulation of abnormal amyloid plaque and neurofibrillary tangles in the brain, leading to the death of brain cells and resulting in progressive cognitive decline.
The Clinical Professional Consultant of the Division of Neurology in CU Medicine’s Department of Medicine and Therapeutics stated that memory complaints are common among middle-aged and elderly people, and are often considered a sign of Alzheimer’s disease.
It is sometimes difficult to make an accurate diagnosis of Alzheimer’s disease based on cognitive tests and structural brain imaging. However, methods to detect Alzheimer’s pathology, such as an amyloid-PET scan or testing of cerebrospinal fluid collected via lumber puncture, are invasive and less accessible.
To address the current clinical gap, CU Medicine has led several medical centres and institutions from Singapore, the United Kingdom and the United States to successfully develop an AI model using state-of-the-art technologies which can detect Alzheimer’s disease using fundus photographs alone.
Studying disorders of the central nervous system via the retina
The S.H. Ho Professor of Ophthalmology and Visual Sciences and Chairman of CU Medicine’s Department of Ophthalmology and Visual Sciences explained that the retina is an extension of the brain in terms of embryology, anatomy and physiology. In the entire central nervous system, only the blood vessels and nerves in the retina allow direct visualisation and analysis.
Thus, it is widely considered a window through which disorders in the central nervous system can be studied. Through non-invasive fundus photography, a range of changes in the blood vessels and nerves of the retina that are associated with Alzheimer’s disease can be detected.
The team developed and validated their AI model using nearly 13,000 fundus photographs from 648 Alzheimer’s disease patients (including patients from the Prince of Wales Hospital) and 3,240 cognitively normal subjects. Upon validation, the model showed 84% accuracy, 93% sensitivity and 82% specificity in detecting Alzheimer’s disease. In the multi-ethnic, multi-country datasets, the AI model achieved accuracies ranging from 80% to 92%.
Accessibility, non-invasiveness and high cost-effectiveness of the AI model using fundus photography help the detection of Alzheimer’s cases both in the clinic and the community
A Professor of Medicine and Director of the Therese Pei Fong Chow Research Centre for Prevention of Dementia at CU Medicine stated that in addition to its accessibility and non-invasiveness, the accuracy of the new AI model is comparable to imaging tests such as magnetic resonance imaging (MRI).
It shows the potential to become not only a diagnostic test in clinics but also a screening tool for Alzheimer’s disease in community settings. Looking ahead, the team aims to validate its efficacy in identifying high-risk cases of the disease hidden in the community, so that various preventive treatments such as anti-amyloid drugs can be initiated early to slow down cognitive decline and brain damage.
The Associate Professor in the Department of Ophthalmology and Visual Sciences at CU Medicine said that in addition to applying novel AI technologies in the model, the team also tested it in different scenarios. Notably, their AI model retained a robust ability to differentiate between subjects with and without Alzheimer’s disease, even in the presence of concomitant eye diseases like macular degeneration and glaucoma which are common in city-dwellers and the older population.
Their results further support the hypothesis that the team’s AI analysis of fundus photographs is an excellent tool for the detection of memory-depriving Alzheimer’s disease. To move this research towards clinical application, the team is developing an integrated, AI-based platform to combine information from both blood vessels and nerves of the retina captured by fundus photography and optical coherence tomography for the detection of Alzheimer’s disease. Their findings should provide more evidence to move AI from code to the real world.