The OECD has published a detailed report looking at how artificial intelligence is affecting global economies and societies. The report considers the acceleration in AI investment and the growth of startups.
The new OECD report is titled “Artificial Intelligence in Society“, issued on June 11, 2019. The report charts the acceleration in artificial intelligence investment since 2016, particularly in the areas of Canada, China, the European Union, Israel and the U.S. As a sign of growth in investment, the report shows how artificial intelligence startups have attracted 12 percent of global private equity investments in the first half of 2018, a figure that is up from just three percent in 2011.
The report additionally looks at the different sectors adopting artificial intelligence systems, the policy challenges of the technology, and issues like risk management and approaches to transparency. This is tune with the focus on how the technology affects society found in the report.
While it is acknowledged that artificial intelligence adoption can generate productivity gains, improve well-being and help address global challenges, such as climate change, resource scarcity and health crises; at the same time, artificial intelligence applications raise questions and challenges related to human values such as fairness. There are also considerations of human determination (self-will), privacy, safety and accountability.
The report follows on from the OECD, together with partner countries, formally adopting a new set of ‘Principles on Artificial Intelligence’. This activity took place at the Organization’s 2019 Ministerial Council Meeting on May 22 in Paris.
The goal of the new report is to help to construct a shared understanding of artificial intelligence and to encourage dialogue on important policy issues, like labour market developments and upskilling for the digital age. There are other issues like privacy, accountability and the responsibility, security and safety questions that artificial intelligence generates. These form part of a section of the report titled “Public policy considerations”.
An interesting section of the report, which runs to 152 pages, it titled “AI applications”. This section considers ten areas that are seeing a rapid uptake of artificial intelligence technologies. These areas are: transport, agriculture, finance, marketing and advertising, science, health, criminal justice, security, the public sector and augmented/virtual reality. The report looks at the benefits in these areas such as raising the efficiency of decision making, saving costs and enabling better resource allocation.
The report also looks at the big investment in startups, which is running somewhere between $26 billion to $39 billion, with three-quarters of this investment coming from big technology companies – primarily: Google, Apple, Baidu, Facebook, Amazon, Intel, Microsoft, Twitter and Salesforce.
The biggest sectors within which artificial intelligence startup companies are developing are cybersecurity (for example, Amazon and Oracle purchased Sqrrl and Zenedge, respectively); autonomous vehicles; and healthcare. While China and the U.S. are the biggest areas for startup investment (ahead of the European Union in third place), the most rapid growth has occurred in Israel, which has seen the share of investments in AI startups jump from five to 25 percent between 2011 and the first half of 2018.
Canadian startup Deep Genomics uses AI to speed up drug discovery
One of the biggest challenges pharmaceutical companies face is with the time taken to discover new drugs, develop them and get them to market. This lengthy process is punctuated with false starts. Startup Deep Genomics uses AI to accelerate the process.
Canadian startup Deep Genomics has been using artificial intelligence as a mechanism to speed up the drug discovery process, combining digital simulation technology with biological science and automation. The company has built a platform which uses machine learning to delve into the molecular basis of genetic diseases. The platform can analyze potential candidate drugs and identify those which appear most promising for further development by scientists.
The drug development process is dependent upon many factors, such as those relating to combining molecules (noting the interactions between hundreds of biological entities) and with the assessment of biomedical data. The data review required at these stages is highly complex. For these reasons, many researchers are seeking algorithms to help to extract data for analysis.
According to MaRS, Deep Genomics is addressing the time consuming element involved in the initial stages of drug discovery. The artificial intelligence system that the company has designed is able to process 69 billion molecules, comparing each one against around one million cellular processes. This type of analysis would have taken a conventional computer (or a team of humans) many years to run the necessary computations.
Within a few months, Deep Genomics AI has narrowed down the billions of combination to shortlist of 1,000 potential drugs. This process is not only faster, it narrows down the number of experiments that would need to be run, saving on laboratory tests and ensuring that only those drugs with a high chance of success are progressed to the clinical trial stage.
This type of system goes some way to addressing the lengthy typical time to market, which stands at around 14 years for a candidate drug; as well as reducing the costs for drug development, which run into the billions of dollars per drug.
Health service partners with Alexa to provide medical support
The U.K. National Health Service (NHS) is to partner with Amazon’s Alexa in order to provide health information. This is being piloted as an alternative to medical advice helplines and to reduce the number of medical appointments.
While the U.K. NHS is much admired around the world as a free-at-the-point-of-use healthcare system, health officials are always keen to find ways to reduce the strain on the systems, especially relating to medical visits where the process of booking appointments and waiting times for sessions with doctors can be lengthy. The average time to obtain a non-medical emergency appointment with a general medical practitioner is averaging around two weeks.
Although a non-emergency medical helpline is active (accessed by dialling 111), plus an online system, health officials are keen to explore other ways by which the U.K. population can access medical services. For this reason, NHS England is partnering with Amazon.
The use of Alexa voice technology not only offers an alternative service for digitally-savvy patients, it provides a potentially easier route for elderly and visually impaired citizens, as well as those who cannot access the Internet through a keyboard, to gain access to health information. This fits in with a new initiative from the U.K. Government called NHSX, which is about the NHS Long Term Plan intended to make more NHS services available digitally.
As PharmaPhorum reports, Alexa can now answer questions such as “Alexa, how do I treat a migraine?” and “Alexa, what are the symptoms of flu?”
Outside of the U.K., Amazon is working with several healthcare providers, including digital health coaching companies, in order to launch six new Alexa healthcare ‘skills’. According to Rachel Jiang, head of Alexa Health & Wellness: “Every day developers are inventing with voice to build helpful and convenient experiences for their customers. These new skills are designed to help customers manage a variety of healthcare needs at home simply using voice – whether it’s booking a medical appointment, accessing hospital post-discharge instructions, checking on the status of a prescription delivery and more.”
Chatbots are revolutionizing retail
This story originally appeared on Digital Journal.
The rise in chatbot use is just one example of the AI revolution online retailers are facing. A key consideration that retailers face is using the technology to create individualized experiences to retain customers and drive sales.
A recent study by Juniper Networks indicates that retail sales from chatbots will nearly double annually, reaching $112 billion by 2023, which is a lucrative outcome of the automation of customer sales and support processes. Chatbots are just one example of how technology is being used to create intelligent content and perhaps what is becoming the future of e-commerce.
Online retailers are also investing big in artificial intelligence-driven systems, such as smart CMS, that allow them to deliver individualized experiences, an increasingly crucial part of customer retention and driving sales.
Rasmus Skjoldan, chief marketing officer of Magnolia CMS, discusses with Digital Journal how new AI/ML features in modern technology are changing the way retailers create an online customer experience.
Digital Journal: How is artificial intelligence impacting on retail?
Rasmus Skjoldan: Retail is a seasonal industry, and because of that, there can be large peaks and valleys in customer questions and associated ticket volume throughout the year. This is a perfect use case for where digital transformation can have a massive impact, because digital communication channels and automation in the form of chatbots and AI can help alleviate the pain associated with seasonal upticks in volume.
It can be hard to scale live, phone-based support systems for such variations in traffic, and because of this, customers often have to wait on hold to get help — a terrible experience. Messaging, on the other hand, allows conversations to continue without the customer having to wait around for a live agent, and bot-based automation can take on a lot of the heavy lifting for customers with routine requests like checking on a shipping status.
DJ: How important are chatbots becoming for retail, and what advantages are retailers seeking to leverage from chatbots?
Skjoldan: The biggest retailers are able to automate so much more in this era of digital transformation because they can integrate bots with back-end systems, like an existing CRM or shipping provider. These integrations allow them to remove the agent from a lot of conversations. By assigning common inquiries to chatbots, retailers can remove some of the burden from live agents. In terms of staffing around the holidays, bots can handle a lot of the increased volume, so that retailers don’t have to hire as many seasonal agents.
DJ: Generally, how do customers react to chatbots?
Skjoldan: Customers want their issues to be resolved quickly and effortlessly. If a chatbot is able to accomplish that, then most customers are happy. Frustrations arise when chatbots misinterpret the issue at hand. It is important for brands to use chatbots to cater to the customer’s desire for convenience, while also offering the option to speak to a real agent when the chatbot becomes an inconvenience.
DJ: What are the main limitations with chatbots?
Skjoldan: Many chatbot vendors today are relying on a purely conversational bot experience, and it can be very difficult and time consuming to train these AI models. To circumnavigate this issue, organizations can use conversational AI technology to classify the ticket, coupled with decision trees that are deterministic and far more effective in resolving use-case specific issues.
DJ: How can technology help to overcome these limitations?
Skjoldan: If retailers keep their automation and bots decision tree-based, then the retailers are controlling the conversation. This is a simpler form of technology that is easier to manage. If AI determines that the customer inquiry can be handled through an existing bot workflow, then your customer moves through a set of predetermined tasks instead of the customer trying to have a conversation with a bot. If the customer’s question does not match a predetermined workflow, the back-end software will connect them with an agent.
DJ: What will customer service look like five years from now?
Skjoldan: The customer service industry is already seeing massive improvements in the efficiency of CX through automation, and I believe in the next five years, that progress will only be magnified. Brands will automate more than 90% of their customer service and reserve agents for their most complex issues. To get there, the industry will need more data scientists, engineers and analysts to maintain models and create bots that will ensure a great customer experience. Automation will work towards improving efficiency of service — and more significantly increase revenue for brands as a result.
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