Value Vector: The Cognitive Explosion, Ethics and How Work Is Changing - Digital Workforce Summit impressions
We’re on the cusp of massive changes powered by Cognitive Computing, reaching across nearly every industry and occupation. Cognitive Computing broadly includes Machine Learning and Artificial Intelligence – systems that are able to learn and improve on their own without human intervention. The declining costs of cognitive-friendly GPUs (Graphics Processing Units) and FPGAs (Field Programmable Gate Arrays) make it increasingly practical to embed cognitive capabilities into connected edge devices such as cameras, drones, gateways, IoT appliances, automobiles and wind turbines. It follows that as technological capabilities increase, the presence of technology in our everyday life is inevitable, leading to a greater focus on the human machine interface.
Momenta recently attended the Digital Workforce Summit in New York, hosted by IPSoft, to focus on the uses of AI, the market opportunities and challenges. Here are some of the insights on offer and how Cognitive Computing is changing and challenging Connected Industry.
Technology is getting more accurate, powerful and aware – and industry is interested
Cognitive computing is becoming more accurate: error rates for image labeling have fallen from 28.5% to below 2.5% since 2010 (below human accuracy of 5%) in the annual ImageNet competition. Stanford University has found that voice recognition is now 3X faster than typing. Devices at the edge will increasingly be able to learn and optimize real-time decision-making while leveraging deeper analyses of historical data in the cloud. Companies such as Ocado are working to develop a robot assistant trained to understand maintenance tasks so that it can either pro-actively, or as a result of prompting, offer assistance to automation maintenance technicians performing routine and preventative maintenance, and other robots are teaching skills amongst themselves.
There's also active corporate engagement - machine learning patents grew at a 34% CAGR from 2013 to 2017. Investments in Artificial Intelligence and Machine Learning are expected to continue pace - with IDC forecasting spending growing from $12 billion in 2017 to $57.6 billion by 2021. Financial institutions will spend $590 billion on IT this year with growing interest in AI - Bank of America is investing $3 billion in virtual assistants, BNY Mellon is reducing back office processing time.
Awareness is resonating: a Harvard Business Review study found that nearly three-quarters of executives believe AI will transform business within 3 years and that the application will enable the recovery of 6.2 billion hours of employee productivity annually. There is increasingly the view that AI is exponentially improving how to analyze business challenges and match with the best solutions.
Workforce Summit highlights how AI is already impacting businesses
Sponsor of the Digital Workforce Summit, IPSoft, has developed Amelia, a digital agent that responds to inquires based on 60 different types of human interactions. The use of the Amelia agent has been able to reduce the length of calls, improve customer satisfaction and lower costs. IPSoft forecasts that by 2025 you will pass someone in the corridors and not tell if it’s a human or an android.
There were also several examples of how companies are using AI to improve the customer experience. Matt Tomlinson director of Customer Experience Labs at Electronic Arts, the gaming company discussed how the company uses AI to improve entertainment for their gamer customers. They use several levels of AI - first are Chatbots for simple queries, and going deeper, conversational AI can have ongoing dialogues in natural language. EA was able to improve interactions with human agents in meaningful way.
Mike Brady former CTO of AIG spoke about how AI helps with insurance processes that are NIGO – Not In Good Order – tasks that a data ingestion team cannot process. In his view, people do not make the best middleware because they introduce errors and delays into processes. By looking at the application of AI to replace teams of people in back office processes, this creates benefits in speed by orders of magnitude. Accuracy can be close to 100%, while humans top out typically around 90-96%.
Life 3.0 – exploring the ethics of AI as we design the future
Max Tegmark of MIT and author of Life 3.0 spoke about how AI and technology can change the nature of work. Tegmark is a physicist, and highlighted Apollo 11 as an example of successful science. Entrepreneur Jan Tallin points out that it’s not enough to make technology powerful - we need to steer it. In his view, intelligence is simply the ability to accomplish complex goals. This includes biological and artificial intelligence. AI can create new faces, it can beat humans at the game of Go. AlphaZero beat even AI researchers. In response critical decision making needs to follow about the capabilities we imbed into technology and who decides what is ethical and for what purpose.
How far will this go- and when?
Tegmark depicted AI as water on a landscape potential flooding many different tasks. The concept of AGI (Artificial General Intelligence) represents the intelligence of a machine that could successfully perform any intellectual task that a anhhbeing can. It is a primary goal of some artificial intelligence research and a common topic in science fiction and future studies. Artificial general intelligence is also referred to as "strong AI", "full AI" or as the ability equivalent capabilities to humans. If we reach a level of human equivalence, recursively self-improving AI could accelerate progress. Rodney Brooks thinks AGI will not happen for centuries, and Demis Hassabis of DeepMind thinks we will achieve AGI within decades.
AI is the water flooding human tasks (with Max Tegmark)
What will be the role of intelligence?
According to Tegmark, we are going to need a new approach – we historically learned from mistakes with cars and fire. With nuclear power, synthetic biology and AGI we need to engineer safety from the beginning. This is safety engineering – which he recommends as the strategy to frame the development of AI.
The 23 Asilomar Principles were signed last year as a framework for ethical development. Tegmark highlighted that we should avoid an arms race and lethal autonomous weapons. We need to mitigate wealth inequality. We also need to invest in AI safety research. We need to ensure that machines understand, realize and maintain our goals. Tegmark argues that we can’t bungle into the future without being appropriately prepared. He argues that we want technology that does not overpower - it empowers.
The future of humanity? (Max Tegmark)