Artificial intelligence ('AI') is more and more sneaking up into our daily activities. Anyone using Google, Facebook or a Microsoft product knows this. Not every enterprise is using AI at the same pace. Has your organization started looking into using AI yet? Do you have any clue on how to tackle and implement AI in your organization?

Despite all the panicky warnings seen in the mainstream media, AI will not be taking over and automating peoples' jobs. AI will be replacing manual tasks, not job categories. However, something very important is missing from the picture: the involvement of the employees who will be charged with making AI and data-driven enterprises work. AI is only ramping up demand for the human talent needed to guide AI systems to engage in tasks relevant to the business, monitor and maintain the fairness and actionability of AI decisions, and to build, program, update, and ultimately retire these systems. That's one of the takeaways of Deloitte's latest research on the state of AI, which finds a lack of employee input into the ways AI will be deployed and what it will deliver.

KAUST scientists have used deep learning algorithms to accelerate the examination of thousands of years old, giant, stone rectangles in the Saudi desert. "An international study showed that the huge, mysterious stone structures known as'Mustatil' (Arab word for'Rectangle') in northwestern Saudi Arabia, are among the oldest archeological ruins in the world," Saudi Minister of Culture, Prince Badr bin Abdullah bin Farhan, said in a tweet in 2021. These historic sites, which are around 7,000 years old, bewildered researchers and scientists who have long sought to determine their nature and the reasons behind their construction. A recent study by the University of Cambridge suggested that these huge structures, comprising chambers, entrances, and seats, are more complicated than expected. For quicker results, researchers at the King Abdullah University of Science and Technology (KAUST) have used an artificial intelligence network to carry out a detailed geological survey in the region, which hasn't been sufficiently studied so far.

It is notable, responsive, and appropriate that the majority of the Initiative projects had various interdisciplinary aspects to them--either in their teams or in the people they convened. Grantees felt that such interdisciplinarity was important to continue and in the long term the community will be healthier and more resilient for this. While the "diversity disaster" in the broader AI field is well known.7 Within the sub-field of AI ethics and governance, grantees noted that a field that relied on the same voices, geographies and, often, institutions would result in missing perspectives. With 15% of grantees being non-US based8 and 80% of funding support academic institutions, on this front, and in line with their international ambitions9 the Initiative could have done more. There remains an imperative to push for substantive diversity of thought and experience, both within geographies and across them.

The use of artificial intelligence ("AI") and machine learning in the workplace is growing exponentially – and specifically in hiring. Over the last two decades, web-based applications and questionnaires have made paper applications nearly obsolete. As employers seek to streamline recruitment and control costs, they have jumped to use computer-based screening tools such as "chatbots" to communicate with job applicants, to schedule interviews, ask screening questions, and even conduct video conference interviews and presentations in the selection process. Employers of all sizes are creating their own systems, or hiring vendors who will design and implement keyword searches, predictive algorithms and even facial recognition algorithms to find the best-suited candidates. The algorithms in these computer models make inferences from data about people, including their identities, their demographic attributes, their preferences, and their likely future behaviors.

A career in technology should be taught from the lower level of education. Once the students feel attracted to the influence of artificial intelligence and its innovations, they take up tech-based courses to quest their thirst. That is what Indian Institute of Technology colleges in India do. First set up in 1951 in Kharagpur, IITs are now located at 23 places across the country. Indian Institute of Technology colleges are educating students with practical knowledge by taking up artificial intelligence initiatives.

The rush is on to implement in a battle for competitive advantage. However, in the haste to implement, some organizations are stumbling because their initiative lacks a solid foundation. "People want to solve problems with AI just because it's AI and not because it's the best solution," said Scott Zoldi, chief analytics officer at analytics decisioning platform provider FICO. "It has to be soup to nuts. How are we going to develop AI from a governed perspective of having a governance process that talks about the data, the success criteria and the risks from both a project perspective and an ethical perspective?"

Artificial intelligence (AI) is already embedded in a range of digital services. Voice assistants such as Alexa, car routing or content translation all involve machine learning – the most popular form of artificial intelligence technology. There are many warnings these days about AI, such as the ethics behind these machine driven decision systems or threats of automation and the loss of many jobs. Very little is reported about how artificial intelligence can improve public services and can have positive social impact. Smart algorithms combined with cloud computing power allow unprecedented forms of data analysis that would take much longer if humans were doing it.

In 2018, the Bank of Thailand began developing new artificial intelligence (AI) and machine learning tools across a number of its core business lines. Natural language processing, which helps institutions analyse unstructured datasets, has been its focus in recent months. "In the past, we typically studied behaviour and culture of the boards of directors of financial institutions through interviews and surveys, which are very qualitative and subjective," says Wanpracha Chaovalitwongse, senior director of the data management and analytics department. The central bank developed an AI system to analyse board meeting minutes of financial institutions. The tool can automatically identify topics of discussion and quantify the participation level and participation'mode' of each board: enquiring, reporting, commenting and requesting action.

With an esteemed line-up of international speakers, drawn from across Europe, Asia and the Middle East, the forum will inform and provide insight to all participants during the one-day programme.