Tehran(Bazaar)-Farahnaz Sepehri: Richard Foster-Fletcher and Animesh Jain in an interview with Bazaar News Agency, talked about the challenges and development strategies in the field of artificial intelligence
Richard Foster-Fletcher is the Founder and Executive Chair of MKAI, the inclusive Artificial Intelligence Community and leads the MKAI Centre for Digital Trust. He is a graduate of the MIT AI Business Strategy Course, and his first book will be published in 2023 by Bloomsbury about the economics of digital trust. Richard leads several large scale sustainability projects and he has collaborated with the United Nations to support their AI and Digital Transformation via his media work.
Animesh Jain is a Research Manager at MKAI. He has completed his MA in international security with concentrations in China & East Asia and Diplomacy from Sciences Po, Paris. He has previously worked with organizations including Kubernein Initiative, Tianjin Intertech Corporation, AI Policy Labs, National Skill Development Corporation and Observers Research Foundation in different capacities.
MKAI is an inclusive community of diverse thinkers that, together, are shaping the future of Ethical Artificial Intelligence. The vision is to connect diverse minds and deliver impactful community-led projects that make artificial intelligence (AI) more inclusive, accessible and rooted in sustainable human values.
The MKAI.org community supports global projects encompassing three distinct areas: 1. Digital Ethics and Trustworthiness, 2. Digital Inclusion, and 3. Digital Citizenship. MKAI acts as a not-for-profit organisation and the work is intended to create a kinder, fairer and more sustainable world.
Following is the full text of the interview:
Bazaar: How does artificial intelligence affect the efficiency of industries?
Richard Foster-Fletcher
Foster-Fletcher: Artificial Intelligence (AI) is making great strides in improving the efficiency of industries, leading to better performances. AI systems enable greater efficiency by enhancing human capabilities and providing real-time insights, transforming how companies run their production lines. Not only does this improve efficiencies, but it also allows companies to develop new production, operations and distribution capabilities. In addition, machine automation also facilitates design and product innovation while providing critical information to help managers make more informed business decisions.
For example - by optimising supply chain planning processes, manufacturers can identify patterns of demand for various products, including critical variables like market behaviour, political or socio-economic developments etc. AI can also help manufacturers forecast future market demand, which impacts how raw materials are sourced, helping the manufacturers make necessary financial and recruitment decisions.
Animesh Jain
Jain: Moreover, companies that implement a digital infrastructure benefit from the opportunity to fully embrace the skills and knowledge of their best assets - people. AI makes the processes more effective, not by replacing people but by filling in the gaps in people’s skills. By working together, the collaboration of people and automated machines makes work less manual, tedious and repetitive, hence increasing accuracy and efficiency. By embracing a plethora of established and emerging digital technologies, companies can significantly transform their operations, control costs, reduce downtime and improve profits. For example, predictive maintenance can reduce machine downtime by around 30-50% and increase the machine life by 20-40%.
Thus, AI is proving to be a critical enabler of the Fourth Industrial Revolution and will ultimately empower the industries and manufacturing and continue to be the backbone of the global economy. AI, especially in manufacturing, enables factories to get ready for the future.
Bazaar:What are the important factors in the better performance of artificial intelligence in business?
Jain: Three significant factors impact the improvement of AI in a business: Data, Diversity and Leadership.
There is a vast amount of data that a business generates in its different processes, and it is essential to aggregate, catalogue and use that data to solve business problems. How we govern the data we produce is important - data must be consistent, reusable, transparent, trustworthy and open; it is vital to have a strategy to store and use data. But relying on data governance policies is not enough; leaders need to understand the processes in the business and be familiar with how each process can effect or influence the outcomes of the AI algorithms. Consequently, leadership is vital for the better performance of AI in a business.
Foster-Fletcher :AI systems are based on learning from data, and if the data is biased in the designer's favour, it can have enormous ramifications. In addition, AI is already present in places you may not be aware of. Many countries' surveillance cameras, for example, already have advanced AI technology that assesses every second of citizen movement. It can be harmful to some people if there is implicit bias in the system. Leaders of companies and countries must take an active role in making sure that when the AI systems in their jurisdiction make a call, it can make accurate decisions, thus diversity is very important.
Governments and Organisations need to develop guidelines that mandate ethical AI practices. Incorporating feedback from people of all perspectives, backgrounds, and lifestyles into the design of AI systems must become the norm. The power of mass consumer software is now concentrated in the hands of a few large software corporations. These corporations have complete control over and influence over the development of items that will affect the vast majority of the world's population.
Technology is changing our way of life and human behaviour in ways we can't predict. AI has the potential to create self-driving cars, robots that can communicate with us, and much more. As a result, diversity in AI is required to eliminate prejudice in the systems' foundations.
Bazaar:What measures should governments take to facilitate the use of industrial intelligence?
Jain: Governments should invest in, and provide infrastructure to support foundational research in industrial intelligence. Like by increasing the number of AI researchers and skilled graduates, improving national AI research capacity, and fostering national competitiveness in AI with global ambitions. Governments should also direct their research funding to emphasise data and AI across a range of domains. AI competitiveness strategies that emphasise broad-based AI and data literacy are important to help the citizens of a country to understand and fully participate in new economic opportunities. This capability must be built and strengthened through diverse teams including humanities graduates for creating a responsible AI that benefits all.
Foster-Fletcher : For responsible AI to deeply penetrate an economy and society, Governments can build data centres, thereby accelerating their own transition to the cloud. Then opening up those spaces to non-profit and social good organizations and SMEs, Government can work with technology companies in public-private partnerships to provide services. They can create a platform to offer data sets for others to build upon and use. They should embrace open standards and be willing to allow open APIs on their data to foster innovation and competition in public and private sectors.
Governments must also pursue digital and data diplomacy; this includes active participation in local and global debates about this technology's uses, limits, and ethics. Furthermore, they must insist on attaching responsible, ethical AI to the objectives. The risks associated with AI, such as harms, prejudices, exclusions and biases, require Governments to promote the responsible design, development, and use of AI to ensure their citizens are safe and protected whilst the country is still competitive. In the future, country leaders must ensure that artificial intelligence developments carefully balance the benefits to GDP with the well-being of their citizens.
Bazaar:What are the challenges in using AI for organizations? (about cost, skill, infrastructure and etc)?
Jain: The big challenge with AI implementation is the abundance of data. An organisation either don't have enough data or has so much that it becomes overwhelming and not actionable. In most cases, businesses can either extract specific data from systems or identify the right set of data - it can be quite challenging to determine which data to use. If the correct process is not known, it becomes tough to improve it, and AI won't highlight patterns and outliers. Moreover, data security and storage also become significant issues for businesses when using large volumes of data. Therefore, it also creates problems related to data security. With this in mind, companies need to implement the right data management environment for implementing AI.
Integrating AI into existing business systems is another major challenge for most businesses. As AI-based solutions have a high level of computational speed, substantial infrastructure and high-end processors are required for building a flexible infrastructure that is compatible with AI-based solutions.
Foster-Fletcher :Moreover, rolling out successful AI projects takes time and training. As a result, AI does not show immediate effects as it is a process and requires capital investments which can be too sizeable for some SMEs. So, an effective strategy and pragmatic leadership are required from the project's inception. Moreover, regulation often proves to be the biggest hurdle of all. As national AI strategies and policy initiatives rarely focus on SMEs. But if we can support SMEs, start-ups, entrepreneurs, and research institutions focusing on innovative firms, we can see significant changes in national economies.
Bazaar:How artificial intelligence affects the economy?
Jain:Today's leading economic experts see AI as an engine of productivity and economic growth. AI can vastly increase the efficiency of a country's industries and workforce and make the decision-making process more informed by analysing large amounts of data. In addition, it can generate new revenue streams by helping in creating new innovative products and services,markets and industries, thereby boosting consumer demand. As a result, most studies emphasise that AI will have a significant economic impact. According to specific forecasts, by 2035, AI could double the annual global economic growth rates.
AI can drive a country's economic growth in three important ways: Firstly, AI enables an increase in labour productivity (by up to 40 %) due to innovative technologies enabling more efficient workforce-related time management. Secondly, AI can create a virtual workforce that can solve problems and self-learn in changing economic environments/requirements. Thirdly, national economies will benefit from the diffusion of innovations in different sectors and industries, generating new revenue streams.
Foster-Fletcher : But AI may also widen the gaps between countries, reinforcing the current digital divide. Every country would need a different strategy and response due to the difference in AI adoption levels. Depending on the choices that governments make to strengthen AI-related foundations and enablers and capabilities to manage the transition of countries can proactively change their paths. Some countries are already trying to shape bold paths for the future with their national strategies in place to become part of the global AI supply chain and are investing heavily there.
Through our community, which encompasses over 55 nationalities and promotes diverse thinking, MKAI is uniquely positioned to help governments and businesses navigate this dynamic industry.
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