In a downturn, "it's very easy to cut things that are new, that others do not understand, that are yet to prove value," said Katia Walsh, chief strategy and artificial intelligence officer at Levi Strauss & Co. Five years ago, some companies made huge investments in AI without having enough high-quality foundational data to train and run the algorithms. That left executives underwhelmed by the results and disillusioned, according to Todd Lohr, KPMG LLP's U.S. technology consulting leader. Costly early projects failed to pay off, especially in sectors like healthcare, where the difficulties of coalescing and structuring data are complex, Mr. Lohr said. Additionally, many companies approached AI without a sense of what it could realistically do, said Andrew Ng, founder and chief of startup Landing AI and a former chief scientist of Baidu Inc.

Sia Partners is a specialist Management Consulting firm in 1999 and has grown into a global firm with approximately 2500 employees and annual revenue exceeding $400m. Our culture is strongly orientated towards high-quality expertise and delivering excellent results and outcomes for our clients, which include a wide range of multinational companies. Our global presence and our expertise in more than 30 sectors and services allows us to accompany clients worldwide. Using innovative technologies such as our own in-house apps, social networks, and digital tools, we provide a truly integrated global service. Through Consulting for Good, we put our expertise at the service of our clients' climate objectives and make sustainable development a performance lever for our clients.

AI is approaching the next level of maturity, coming out of the hype cycle, says Gartner. Its adoption is expanding across industries beyond automation to building new-generation intelligent products and services for business growth. However, half of them acknowledge that they don't have skilled talent to make the most of AI advances. This is where experienced AI consulting firms come in to help. The market of AI consulting is vast, ranging from tech giants like IBM and Accenture to Big 4 firms and smaller-scale innovators.

Artificial intelligence has seen a slew of investments throughout the Middle East, with many nations seeing the tech as playing a key role in creating a more sustainable future

Walking back from a business meeting, management consultant Emilia Higashi quickly developed blisters on her feet. She figured there had to be better way to make women's shoes – ones more comfortable and also sustainable, made from plants instead of animal or petroleum products. Soon, she was researching in Italy at the world's biggest footwear trade show. She fell in love with a design called Saccheto, or little sack, that has minimal seams and fits almost like a sock. Then, she looked worldwide for sustainable plant-based materials, including "leathers" made from wine residues, pineapple fibers, cactus and even algae.

There is mounting public concern over the influence that AI based systems has in our society. Coalitions in all sectors are acting worldwide to resist hamful applications of AI. From indigenous people addressing the lack of reliable data, to smart city stakeholders, to students protesting the academic relationships with sex trafficker and MIT donor Jeffery Epstein, the questionable ethics and values of those heavily investing in and profiting from AI are under global scrutiny. There are biased, wrongful, and disturbing assumptions embedded in AI algorithms that could get locked in without intervention. Our best human judgment is needed to contain AI's harmful impact. Perhaps one of the greatest contributions of AI will be to make us ultimately understand how important human wisdom truly is in life on earth.

The 3rd edition of the Montreal AI Ethics Institute's The State of AI Ethics captures the most relevant developments in AI Ethics since October 2020. It aims to help anyone, from machine learning experts to human rights activists and policymakers, quickly digest and understand the field's ever-changing developments. Through research and article summaries, as well as expert commentary, this report distills the research and reporting surrounding various domains related to the ethics of AI, including: algorithmic injustice, discrimination, ethical AI, labor impacts, misinformation, privacy, risk and security, social media, and more. In addition, The State of AI Ethics includes exclusive content written by world-class AI Ethics experts from universities, research institutes, consulting firms, and governments. Unique to this report is "The Abuse and Misogynoir Playbook," written by Dr. Katlyn Tuner (Research Scientist, Space Enabled Research Group, MIT), Dr. Danielle Wood (Assistant Professor, Program in Media Arts and Sciences; Assistant Professor, Aeronautics and Astronautics; Lead, Space Enabled Research Group, MIT) and Dr. Catherine D'Ignazio (Assistant Professor, Urban Science and Planning; Director, Data + Feminism Lab, MIT). The piece (and accompanying infographic), is a deep-dive into the historical and systematic silencing, erasure, and revision of Black women's contributions to knowledge and scholarship in the United Stations, and globally. Exposing and countering this Playbook has become increasingly important following the firing of AI Ethics expert Dr. Timnit Gebru (and several of her supporters) at Google. This report should be used not only as a point of reference and insight on the latest thinking in the field of AI Ethics, but should also be used as a tool for introspection as we aim to foster a more nuanced conversation regarding the impacts of AI on the world.

Despite years of hype (and plenty of worries) about the all-conquering power of Artificial Intelligence (AI), there still remains a significant gap between the promise of AI and its reality for business. Tech firms have pitched AI's capabilities for years, but for most organisations, the benefits of AI remain elusive. It's hard to gauge the proportion of businesses that are effectively using artificial intelligence today, and to what extent. Adoption rates shown in recent reports fall anywhere between 20% and 30%, with adoption typically loosely defined as "implementing AI in some form". A survey led by KPMG among 30 of the Global 500 companies found that although 30% of respondents reported using AI for a selective range of functions, only 17% of the companies were deploying the technology "at scale" within the enterprise.

In the last few years, many asset-intensive organizations, particularly in the mining, power and utilities, oil and gas, and chemicals industries, have turned to industrial Internet of Things (IIoT) and cognitive technologies to help improve a critical area of their business: equipment reliability.1 Asset performance management (APM) programs, which connect data and trigger actions via systems across the business, can play a major part in driving these improvements. According to a 2018 Deloitte survey, oil and gas leaders rated the big data derived from programs such as APM as the most likely to provide the greatest business value.2 However, when asked about how digital technology can be used most effectively within their companies, those same executives ranked APM below both cost reduction in maintenance and operations as well as improvements in safety.3 This seems to reveal a pervasive and narrow view of APM that may miss the connection between asset performance, broader maintenance and operations improvements, and safety. Merely implementing APM software and digitizing existing processes is not likely to improve core operations and obtain the financial results that executive leaders desire (and investors demand).

In today's online market place, visual marketing is an integral part of reaching out to customers. Research show that the human brain is more visual. Up to 80% of people remember what they see compared to only 20% of what they read. This is one of the main reasons why visual content resonates more than written content. It has a greater chance of going viral.