In the early 1980s, presentations about Infosys began with the founders' pointing out India and Bengaluru on a world map. Today, globally listed companies such as Dr Reddy's, Tata Motors, and Reliance Industries have made that redundant. The country is also the third-largest startup nation. A number of its business-to-consumer (B2C) ventures, from e-commerce major Flipkart to ride-sharing platform Ola, are known across the world. Now, a new wave of business-to-business (B2B) startups in niche segments is silently creating a significant impact globally.
This is the fourth in a series of articles I am writing about Māori ethics with AI, Data sovereignty and Robotics. Article 3: Māori Ethical considerations with Artificial Intelligence Systems; Article 2: Māori ethics associated with AI systems architecture and Article 1: Māori cultural considerations with Artificial Intelligence and Robotics. The next planned articles are"Indigenising the Internet" and "Tikanga and Facial Recognition". At the conclusion of this article, are the English, Māori and a Translation into English of the Māori version of te Treaty of Waitangi. There is an international debate about whether we regulate Artificial Intelligence (AI) or assume that AI systems developments will be the better of the wider community.
IMAGE: Peter Foltz, a research professor at the University of Colorado Boulder Institute of Cognitive Science, has developed an app that rates mental help based on speech cues. Thanks to advances in artificial intelligence, computers can now assist doctors in diagnosing disease and help monitor patient vital signs from hundreds of miles away. Now, CU Boulder researchers are working to apply machine learning to psychiatry, with a speech-based mobile app that can categorize a patient's mental health status as well as or better than a human can. "We are not in any way trying to replace clinicians," says Peter Foltz, a research professor at the Institute of Cognitive Science and co-author of a new paper in Schizophrenia Bulletin that lays out the promise and potential pitfalls of AI in psychiatry. "But we do believe we can create tools that will allow them to better monitor their patients."
A surge of new healthcare products from wearable consumer health trackers to diagnostic algorithms promising to improve medical outcomes and costs with artificial intelligence (AI) is prompting physicians and hospital executives to ask a fundamental question: "Are these technologies solving the right problems?" Two ongoing developments add scale and urgency to this important question. The first is a virtual gold rush of technology vendors looking to stake a claim in the healthcare IT market, which is projected to top $390 billion by 2024 according to research firm MarketsandMarkets. The second is what the World Medical Association is calling a "pandemic of physician burnout," caused by a staggering workload of electronic paperwork to document patient care and which is required for insurance coverage, financial reimbursement, and medicolegal liability protection. More than half of clinicians report feeling burned out from the hamster wheel of documentation and reporting tasks that often require spending two hours at a computer for every hour spent in patient care.
There are plenty of reasons for companies to incorporate data science and machine learning into their business. It can allow you to better understand and predict customer behavior, automate repetitive manual tasks, detect errors and anomalies faster, evaluate business decisions with data instead of mere intuition, get an edge over competitors, give marketing campaigns more punch, check a box for investors, attract more talent for the organization, or brag about it at conferences. Many companies face the challenge of building up a data science team from scratch and it can be hard to figure out how to start. In 2016, I was the first hire of a new data science team, with little infrastructure or strategy in place. Over the years, there were many different challenges for us to solve and mistakes to learn from as the team got more and more mature.
Increasingly, insurance companies are leveraging artificial intelligence (AI) and machine learning to optimize processes, reduce costs, and increase efficiency. For example, Ant Financial's Dingsunbao app is able to make damage assessment and provide detailed analysis including claim amount, damaged parts and repair plan by leveraging AI technologies such as image recognition. Similarly, a public insurer in Germany employs an algorithm to manage the large amount of email correspondence by detecting keywords, sorting correspondence according to topics, urgencies and departments, and suggesting next best actions. In addition to unlocking greater efficiencies and lowering costs, AI and machine-learning technologies can also be applied to help insurance companies acquire new customers, cross-sell and grow revenues. For example, AI and machine learning can provide insights to support more effective customer segmentation, automate and personalize product recommendations, and enable more intelligent and customized self-service product research for customers.
A Tysons tech company wants to boost fundraising and marketing efficiency for both non-profits and businesses by using artificial intelligence. BoodleAI (1751 Pinnacle Drive), which eventually branched out to also create GuidonAI, began as a small startup roughly three years ago and managed to expand its client base to include around 30 non-profit groups and businesses. BoodleAI works with non-profits to expand their donor bases, while GuidonAI exclusively works with businesses to boost marketing strategies, France Hoang, the chief strategy officer and co-founder, told Tysons Reporter. Both companies offer predictive analytics to help organizations by taking the clients' pre-existing data and cross-referencing it with more than 500 other data points on each person, using only names and email. All of the data sets are then analyzed by AI to come up with a predictive model that will be tested for power and reliability, according to the company's website.
In our recent blog about 5G, we were sure the advent of 5G "will impact the IoT space dramatically". So here is more on why 5G is being seen as a further catalyst for the IoT industry. The June 2019 edition of the Ericsson Mobility Report forecasts 1.9 billion 5G subscriptions which mean IoT is likely to reach its full potential as 5G becomes its enabler. As there is a surge expected in the number of IoT devices within households (for increased security), 5G will accommodate these devices from close range to long distance, at unmatched speeds while maintaining unbelievable data rates. In the industrial space, 5G will facilitate wireless sensors deployment throughout factories/storage units along with smarter robots, ensuring a seamless transition from hierarchal network design toward a connected one.
Streets swamped by muddy water with garbage floating by, roads impassable. As in previous years, Diamniadio Lake City has not escaped the series of floods that affect some cities in Senegal each rainy season. Indeed, this urban centre is preparing to test, thanks to Artificial Intelligence (AI), a new way of managing urban development. "By taking the Digital Technologies Park of Diamniadio as a reference site, we have carried out modelling and worked on water runoff scenarios in order to channel them and solve these flood problems," Bassirou Abdoul Ba, coordinator of the Digital Technologies Park, told Scidev.Net. This park, covering 25 hectares, is the first experimental phase of the "smart city" under construction 35km from Dakar, the Senegalese capital.
Should the use of artificial intelligence be legislated? It's also a question that can and should be debated, especially when looking at it through the lens of human resources. And those are just a few of the big ones. That said, the purpose of this article isn't to argue for or against the use of AI as an HR tool, but to look at the current state of the legal situation around the technology. This year alone the federal government and several state governments have started to take action on issues related to artificial intelligence.