Projects keep failing, so what’s the
are about delivering an outcome that fixes a business need. Others suggest
projects are to take advantage of an opportunity. Those opportunities usually
are to fix a perceived problem. Those perceptions to fix that future problems still
needs a project to implement them and solve it. Those projects still need to be
fail for many reasons, building on shaky foundations will usually end in failure.
That foundation is a well-defined and explained problem. Problems need to be
clearly identified, stating how the proposed solution will fix it, and showing
a value proposition to the organisation, customer or both. A quantifiable and
demonstratable benefit, as most businesses are there to make money or provide
better services, why would you be doing it?
need to argue the logic for investing both time and money, more importantly
what the pay back will be. Business is about making money, providing a service,
or both. Funds are usually limited, rarely having a lack of opportunity to be
spent on the many challenges facing organisations.
What is the Business Case for this
first, an organisation wants to understand the why of a project. Closely after
that is the how will it be achieved, and how much. But there needs to be a
compelling reason for carrying out the project. Often projects put the cart
before the horse. In other words, they have a new or updated product that will
future proof their organisation, addressing many of the perceived issues that
could be addressed by the many of the new features on offer all presenting
sound arguments. In a world of unlimited resources and funds that would not be
a problem, but that is not the case. Money and resources are a factor of every
business and they are not always limitless.
that fail are usually proposed with all the good intents, the arguments of the
new features all sound good. The biggest issue is that no one hears the same
benefits. This results in different stakeholders with different expectations.
As the projects progress it becomes a feature fest. More is better, right? But
time elapses, costs increase, expectations having been ill defined results in
no one being happy. Time and money start to run out, results are not achieved
and the project grinds to a halt. Does this sound familiar?
Questions are raised
are these projects failing? What went wrong? We had all the governance in place
and it seemed to be working fine, then it all went south. I just don’t understand
problem is there was no real problem being addressed, or that problem was
perceived and not correctly identified. Problems form the foundations of a business
case, needing to be clearly identified, quantified and expressed in a manner
that all parties can agree. Business cases need to clearly explain the intended
problem to be addressed. Identifying problems and explaining the consequences if
they were not addressed. Then describing the benefits that would result in
fixing them, more importantly how that would be proved.
defining the problems and proposed benefit, there needs to be an understanding of
Why invest? – Describe how this investment will benefit the
The Rational – What is the logic for this investment, how
will it be tested and proved that it has delivered the expected results
Who feels that this is a problem – gather views from all
appropriate stakeholders within the organisation through discussion with the
subject matter experts.
Defining the problem
what is perceived as a problem is usually not the problem. To find the real
problem you will need to carry out “root cause analysis”. A good example of
this is a technique commonly referred to as the “5 Whys”. This is an iterative
interrogative technique used to explore the cause and affect relationships
underlying a problem.
What sort of questions should you be
famous quote of Einstein was:
I had an hour to solve a problem and my life depended on the solution, I would
spend the first 55 minutes determining the proper question to ask…
for once I know the proper question, I could solve the problem in less than
stakeholder say is a problem does not necessarily reflect the root cause that
created the problem. Every stakeholder potentially will have different issues
which they consider a problem. Your job is to dig, finding the root cause. You
need to identify both the cause and the consequence to any issue raised as
potential problems. A simple test is called the “so what?”, Similar to the “5
Whys”, which will be covered a little later.
there any evidence that confirms the cause and effect of the identified
problem? What is the priority? Does it need to be addressed now or could it
wait? Is the issue specific to what you are looking at, or should that
perspective be broader?
Example of 5 Whys
the finance director could not understand why his maintenance costs were
increasing on the factory floor. He had sent a directive to the department to
cut costs. He decided to venture down to the factory floor to speak with the
manager and better understand these increases. (His perceived problem)
as the finance director was walking through the factory he noticed a pool of
water on the floor. He called a maintenance staff member to inquire about the
Why is there a pool of water here on the floor? The staff
member pointed out that one of the pipes above was faulty and leaking. (Maintenance
perceived problem) The director then asked for the manager,
Why was that pipe leaking? The manager pointed out the
replacement washer had not sealed properly. Again, the director then asked,
Why did the washer not seal properly? The manager suggested the
washer had possibly failed. The director then asked,
Why did it fail. The manager then suggested the washers were
cheap and that they had a tendency not to last too long. Again, the director
Why were we using cheap washers? I was following the budget directive
to cut my maintenance costs. We then sourced alternatives as our previous
washers were too expensive.
director had found the root cause. In this case there were several perceived
problems. The director had a problem with his costs of maintenance, the staff
member had a faulty pipe and the manager had issues with cheap washers. At
first replacing the pipe potentially could have fixed the problem. But as it
was not the root cause it would have resulted in an expensive fix and the pipe
potentially would have leaked again because of the washer. The root cause for
the pipe was the use of a cheaper alternative. It also highlighted the cost
increase to maintenance had indirectly been because of a cost cutting
define a problem, you will need to consider the downstream effects of what you
and other stakeholders consider to be the problem and what it means to your
organisation. There are two parts to a problem what has caused it and what are
its consequence? Understanding these causes will help you chose how you
respond. The consequences of a problem will help in identifying relevant
benefits. Showing that investment can work to the objectives in this case,
those objectives will later provide an opportunity to identify alternatives.
that are not well-defined make it harder for decision makers, reducing the
chance of success. This can result in projects that results in less than fit
for purpose results. Either too little in the way of funds and resources, or
too many working on low-priorities. The worst case is lack of resources to
solve a major challenge.
is through clearly understanding the problem and benefits from the beginning. This
will enable everyone to be on the same page, agreeing to the same expectations
and results. Aligning results to the organisations priorities and effectively
addressing the right problem. The idea of a well understood problem is that it
will potentially highlight an opportunity for better results.
Explaining the problem
is the elevator pitch, if you were trapped in the elevator with the key
stakeholder who was the approver of the funds needed. How do you relate the
issue in 90 seconds? That pitch needs to clearly identify the issue, providing
the evidence that supports your statement and the solution with definable
measure of success.
that are ill defined can result in benefits that do not align and undermine your
entire argument for the case. Businesses want to understand how much of a
problem it is? The goal being a call to action. It should have both cause and
consequence, answering both the ‘Why?’ And…’ Questions logically linked. A
great starting point is identifying the consequences of doing nothing?
pitch will never be perfect, potentially changing as more information is
gathered. It will be tested against evidence and morph from its original state,
be prepared for change. The challenge is to go into this exercise without any preconceived
solutions. As further evidence is presented it will develop your understanding
and result in a better result, and a stronger foundation to build your case.
Mistakes in identifying problems
people go into identifying problems sure of the solution, especially when it
comes to technology. In the technology space providers and IT specialist believe
their solutions will provide the answers to any problem. Its just a matter of
shoe-horning those problems into that solution.
simply identifying the problem as a system failure, this has a tendency to drive
the results which usually does not align to the facts and the issue. Again, go
back to “so what?”. What is the evidence that will give you a confidence that a
problem exists? You must present that evidence to explain your rational.
note where you found the evidence as you develop your pitch, it’s always harder
if you try to retrofit a problem with evidence. One of the best tests I would
use is called the “Mum Test”, find someone who is not related to the case to
read the pitch and benefits, ask them, “Does this make sense?”. For me, when I
was an interface designer I would as my mother if she could carry out a specific
task using that interface. With no instructions, I would see what she would do
to achieve the results. The idea is to remove the element of assumption, as we
don’t always know who the audience will be, we need to make sure it is clear
without having to be there to explain.
Benefits, what are they?
you understand the problem and its consequence most people will understand the
benefit of doing something about it. A benefit gives a measurable improvement,
showing the value gained. The consequence of a problem helps to identifying the
relevant benefit that lead to your objective.
should clearly align to the problem that links to the results your organisation
is looking to achieve. Explain the impact which credits to the solutions.
Justify the cost of both money and effort which are supported by demonstratable
Measuring those returns
best way to show a return is by having a measure based on current and future states.
Everyone will have a different measure of value, so there needs to be some more
is the old “WIIFM”, (What’s in it for me). How are you going to show the value
you are declaring?
What will be the return to the organisation or its customers?
How will you measure and prove that benefit?
How will you show the connection of the benefit to the results?
are just a few points to consider when defining and showing benefits in a
project. These measures are to be defined with your stakeholders as they are
the people who will confirm the returns on investment (ROI). They need to be
identifiable, measurable and proven.
you define your problems and benefits there is a need to priorities each of
them. It’s not an exercise in the level of investment is directed to fix the
problem but more enabling better decisions between available alternatives,
making sure you get the best bang for your buck. This will enable focus and to
direct both funds and effort in future, more importantly you can control scope.
priorities will enable better and more directed decisions when you may not get
all the funds you expect. A small problem which has Signiant results for an
organisation or its customers, compared to a large problem which has limited
impact will give a signal of investment. But it raises the question to the
larger problem, has it been clearly identified? And are the consequences fully understood.
of these are good questions and will need further examination. This is not an
exact science, but it is a major step in the right direction.
What tool can help with this process?
technique used to ensure robust discussion and thinking is carried out up-front
in a project is Investment Logic Mapping (ILM). It is a great tool to use
before a solution is identified and before any investment decision is made.
provides a way of identifying problems that need to be addressed. This will
identifying benefits hoped to be gained, more importantly how the project will confirm
the rational, showing the realisation of those benefits. The ILM tool is used
for complex investments but is recommended for any project and will enable the
ability to communicate that information on a single page.
Should you use ILM?
organisations trigger this process based on the investment. It is something
that is not compulsory but is recommended especially for complex, high-risk or multiparty
practice it should form the start of all projects, as the output forms the
foundation of your entire business case. The degree and level that you engage
is determined on the size, complexity and value of the project, but the format
and principles will always be useful to defining your problems and how the
benefits will address them.
the project progresses it will increase the project focus and clarity, helping
in defining an agreed scope and result, which will save debate and discussion
later in the project. It will become a powerful tool that will provide you
leverage in justifying your expenses of both funds and effort.
How does it work?
a facilitator, key stakeholders in a couple of workshops will discover:
Your problems and consequences, then
The outcomes and benefits.
These workshops will build an alignment on the purpose of the
investment, it may not necessarily lead to an agreement, but it will be a
What can you expect from an ILM
should expect to have a single page flowchart that will be written in plain
English. It will define your problems to be addressed, potential benefits of
your investment, and how you will confirm those benefits. It will become the
underpinning logic around your project investment.
workshops will be a series of time-limited engagements up to two hours each. It
will bring together the accountable stakeholders for the benefits realisation.
It should be low-cost and low-effort that will produce new information. It will
bring together all available information to enable a better understanding,
leading to better results.
owners need to prepare by checking their evidence, identifying the right
stakeholders for the workshops and offering their opinion and expertise. The
right stakeholders are those who have identified and understood the business
problems, provide the evidence the problem is real, and is responsible for
delivering the benefits. Other stakeholders are those people responsible for
giving advise around the investment to the project. This will increase the
value of the workshops, avoiding the risk of having to start again. Most would
have already been engaged from the start.
problem owner needs to drive the effort, talking with the right stakeholders
and their willingness to contribute will lead the to the right pitch when
presenting your case.
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.
AI and other digital technologies could help solve some of the world’s most important social problems, like climate change, biodiversity loss, food insecurity and risks to public health, among others. Harnessing digital capabilities to promote a transformative system could be a game-changer for a sustainable and equitable global future.
Today’s consumers expect more than great products and services, and businesses are well aware of this. Clients want to feel like they are investing in a reputable, responsible brand. Consequently, the most market-dominant businesses are not merely profitable and have good products but those that have multiple alternate bottom lines – social, environmental and sustainable.
More than 90% of business executives agree that sustainability is crucial to their success. As consumer groups continue to publish reports on the increased desire for more environmentally friendly corporate practices, it is simple to see why green marketing strategies are gaining such importance.
The environment and sustainability are vital components in the strategy and operations of enterprises looking to be more conscientious. Organisations have been taking proactive steps to develop a greener future with their consumers, partners, stakeholders and workers. These efforts include environmental initiatives, community outreach efforts and business practices.
Advancing Environmental Sustainability and Resilience
“Everyone is becoming aware of the necessity for action to attain sustainability,” says Vivek. “There is a growing interest in corporate sustainability and how corporations can strive for it to meet the needs of stakeholders for social, economic, and environmental implications.”
Most businesses are considering ways to contribute significantly, which will need robust investment and efforts. “We see businesses quickening their momentum and considering effective climate innovations. A case in point is how electric mobility companies can be affected by the huge reductions in costs for climate technology.”
Vivek believes it is possible to adapt a company’s digital strategy to mitigate and deal with extreme climate change. Companies must include digitalisation and decarbonisation in their strategy, as industry 4.0 technologies will play a crucial role in meeting the emissions reduction goal.
Digital technologies can increase energy efficiency and decrease fuel consumption across multiple industries and sectors. Digitalisation has the potential to revolutionise the way people and technology interact by helping to analyse and calibrate necessary interventions.
By utilising digitalisation, businesses can identify the emissions sources, whether at the product level, manufacturing unit level, or equipment level. They can then determine the necessary interventions to reduce emissions, such as a change in the manufacturing or personnel settings, and then monitor whether the identified interventions are being implemented.
“Here is where I believe digitalisation and decarbonisation must go hand-in-hand, as this will ensure that industries undergo structural changes and reach their objective,” says Vivek.
Businesses need to be more conscious of the need to be prepared for the energy shift, and he has five relevant steps for how businesses should approach this:
- Develop an understanding of how energy shifts will affect your company;
- Think about a bold and ambitious target, such as considering how big of a carbon footprint reduction they intend to achieve with this energy transition;
- Consider various situations and their effects;
- Create a comprehensive plan that will serve as an overall strategy with well-defined and cascading targets;
- Think about implementation, where companies strike a balance between all the goals, e.g., carbon footprint and profitability
Right now, society is more conscious of sustainability and is calling for companies to shift their carbon footprint and be more conscious about emissions. This is causing profound changes in the corporate and government landscape.
Organisations can work toward more sustainable practices with the aid of corporate sustainability’s economic, social and environmental pillars. Businesses must alter their mindset from just profitability at the expense of the environment to a sustainable and profitable paradigm. There must be interdependence and a greater emphasis on operations and eco-innovation.
Adopting sustainable practices benefits the environment, but businesses have also demonstrated that these programmes can boost productivity, lower costs, make shareholders happy, and a host of other advantages.
“Corporate entities must take the initiative in determining pertinent technologies. Companies must implement technologies to decrease their carbon footprint. They are the ones that will bring about change. Governments can decide the legislation, but unless companies change, it will be difficult to achieve net zero,” Vivek firmly believes.
A green economy is the practice of sustainable development supported by public and private investment in creating an infrastructure that promotes social and environmental sustainability. A green economy refers to an economy in which individuals are increasingly aware of their carbon emissions and are taking steps to reduce them.
A carbon footprint is the total amount of greenhouse gases, including carbon dioxide and methane, that corporations and individuals generate.
There are numerous practical and effective approaches to implementing sustainable technologies at the national level. “I believe that each country will deploy different technologies; the mix of technologies, the adoption rate, and the deployment cost will all be very different. However, each country will need to consider what sustainable technologies are relevant to them, consider implementing them, and consider the reasons for doing so.”
According to Vivek, decarbonisation entails significant economic transformation. When new business opportunities arise in Asia, companies must contemplate how they will be the first to take advantage. To do this, they must seriously consider the technologies and industries they want to innovate in or implement and the various business models they should use to take these opportunities.
There will be an acceleration of the energy transitions if individuals in the nation change their behaviour, the government considers how the empowering regulations should be made, or how businesses decide how they will operate.
Vivek has led several large-scale transformations and new business builds across the region, such as for an energy conglomerate in Indonesia. From this experience, he is convinced that a fundamentally different way of thinking about any business problem is required.
It requires thinking about what the unique value proposition is going to be and thinking about getting new talent to build a business from the ground up. Some of his most memorable moments on this journey include realising the value of having the right talent.
Another thing he learned is that customer preferences change at very different levels. So, thinking about the organisation’s unique value propositions and how customers perceive them becomes very important. For incumbents, choosing different business models can also be essential.
Both private and public organisations are aware that change needs to occur quickly. Resources are becoming harder to come by while demand is rising, necessitating a balance to build a sustainable future. “Green technologies will help the world achieve sustainable levels and make the environment cleaner and safer for everyone.”
Urban Ideas and Solutions Through LKYGBPC
Vivek is on the International Judging Panel (IJP) of the Lee Kuan Yew Global Business Plan Competition (LKYGBPC), a biennial global university start-up challenge held in Singapore.
As a member of the judging panel charged with driving, developing, and upholding the entrepreneurial spirit of the LKYGBPC participants, Vivek is focused on the innovativeness of the solutions, such as how effectively the technology solves the problem.
He also believes that feasibility and how the different technologies are correctly implemented can significantly change the world. “These two parameters will be quite useful in considering how we are selecting, or how I would select various technologies.”
He acknowledges that innovative entrepreneurship talent can be cultivated wider in the broader community through such competitions. These serve as an illustration of how they are fostering innovation and entrepreneurship across society.
The competition is also one example of instilling a culture where the next generation is thinking about how things can be done differently. Competitors explore creative ideas and have a forum where they can share their thoughts, which can be a great example of nurturing innovation.
The competition, which is run by the Institute of Innovation and Entrepreneurship at Singapore Management University (SMU), is centred on urban ideas and solutions developed by student founders and early-stage start-ups. It is positioned as a campus innovation movement that seeks to establish a global startup ecosystem with financial backers, including venture capitalists, corporate oligopolies, and governmental organisations.
“I believe many of our leading schools are doing a great job of instilling a culture where children are thinking about how things can be done differently and what are creative ideas,” Vivek opines.
There are numerous instances throughout the world where the technologies or solutions used by youth or larger communities have truly made a meaningful difference. “But it does take some significant effort to raise awareness and establish a forum where people can discuss their concerns, share their ideas, and obtain the resources needed to solve them,” Vivek concludes.
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.