We have all heard how artificial intelligence is so great. How it will dramatically change our lives and make them better. How computers can outperform humans in just about every way possible.
Are you buying all of this hype?
Personally, I find some aspects of the propaganda troubling. The key strategy of AI is that it is better. But, is it really? Can AI truly outperform humans at critical tasks?
Differences Between Artificial Intelligence vs Human Intelligence
Intelligence can be defined as a general mental ability for reasoning, problem-solving, and learning. Because of its general nature, intelligence integrates cognitive functions such as perception, attention, memory, language, or planning. On the basis of this definition, intelligence can be reliably measured by standardized tests with obtained scores predicting several broad social outcomes such as educational achievement, job performance, health, and longevity. So, let us consider the differences between Artificial Intelligence and Human Intelligence in detail.
Artificial Intelligence is the study and design of Intelligent agent. These intelligent agents have the ability to analyze the environments and produce actions which maximize success.
AI research uses tools and insights from many fields, including computer science, psychology, philosophy, neuroscience, cognitive science, linguistics, operations research, economics, control theory, probability, optimization and logic. AI research also overlaps with tasks such as robotics, control systems, scheduling, data mining, logistics, speech recognition, facial recognition and many others.
Human Intelligence is defined as the quality of the mind that is made up of capabilities to learn from past experience, adaptation to new situations, handling of abstract ideas and the ability to change his/her own environment using the gained knowledge.
Human Intelligence can provide several kinds of information. It can provide observations during travel or other events from travelers, refugees, escaped friendly POWs, etc. It can provide data on things about which the subject has specific knowledge, which can be another human subject, or, in the case of defectors and spies, sensitive information to which they had access. Finally, it can provide information on interpersonal relationships and networks of interest.
Comparison of Brain with a supercomputer
Advantages of Artificial Intelligence vs Human Intelligence:
- Speed of execution – While one doctor can make a diagnosis in ~10 minutes, AI system can make a million in the same time.
- Less Biased – They do not involve biased opinions on decision making process
- Operational Ability – They do not expect halt in their work due to saturation
- Accuracy – Preciseness of the output obviously increases
- Artificial Intelligence has significant dominance in many tasks, especially when it comes to monotonous judgments.
The Big Question
Okay, so now that we have the comparison aspects detailed, comes the real question. Would you trust AI to fly a jet airliner full of passengers to their destination? This question assumes that there are no human pilots involved in the flight?
With all of the advancements in AI and especially in the transportation industry, we are seeing autonomous cars, trains, trucks, and more. So, why not airplanes too?
Perhaps it boils down to two core issues: trust and risk. Maybe these are both the same issue?
Would I trust that AI can pilot an airplane from one city to another? My answer might be yes, it could do that flight. And, maybe it can do it very well, perhaps better than a human crew? But, what would the risk quotation be for such a trip? If the weather is perfect and the airplane is new and operating to optimum levels, the risks could be very low. Maybe even lower then if a human crew was at the controls. However, if you start to consider the potential for variables and the concatenation of these variables, then the risk quotation increases dramatically and I might fear boarding that aircraft. Mix in foul weather, severe turbulence, mechanical failures, disorderly passengers, and a host of other disruptions and my sense of security with an AI piloted aircraft diminished rapidly. Give me back the human crew to resolve these troubles and get me safely back on the ground.
Rather than just ponder this question as black vs white, or AI vs Humans, I must wonder if a hybrid model is better? What if it is not a pure either / or issue, but one where AI augments the human to better enhance the safety of flight?
Well, recent history suggests that even a blended model has challenges. When Airbus demonstrated the first 320 at an airshow, it ended in disaster.
Air France Flight 296 was a chartered flight of a new Airbus A320-111 operated by Air France. On 26 June 1988, it crashed while making a low pass over Mulhouse–Habsheim Airport (LFGB) as part of the Habsheim Air Show. Most of the crash sequence, which occurred in front of several thousand spectators, was caught on video. The cause of the crash has been the source of major controversy.
This particular flight was not only the A320’s first passenger flight (most of those on-board were journalists and raffle winners), but it was also the first public demonstration of any civilian fly-by-wire aircraft. The low-speed flyover, with landing gear down, was supposed to take place at an altitude of 100 feet (33 metres); instead, the plane performed the flyover at 30 feet, skimmed the treetops of the forest at the end of the runway (which had not been shown on the airport map given to the pilots), and crashed. All the passengers survived the initial impact, but a woman and two children died from smoke inhalation before they could escape.
Official reports concluded that the pilots flew too low, too slow, failed to see the forest and accidentally flew into it. The captain, Michel Asseline, disputed the report and claimed an error in the fly-by-wire computer prevented him from applying thrust and pulling up. In the aftermath of the crash, there were allegations that investigators had tampered with evidence, specifically the aircraft’s flight recorders (“black boxes”). This was the first fatal crash of an A320.
Boeing 737 MAX
A new report from the New York Times details a bureaucratic mess, caused by the overhauling of an A.I. system, that it says is responsible for the two fatal Boeing 737 Max 8 crashes in Oct. 2018 and March 2019.
Boeing allegedly introduced “aggressive and riskier” changes to an A.I. system built for safety. Those changes, plus siloed departments and a lack of pilot training and regulatory oversight, reportedly led to the deadly Boeing 737 Max crashes.
Governments around the world grounded Boeing 737 Max planes in March 2019, after an Ethiopian Airlines flight crashed just after takeoff. That disaster unfolded five months after a similar crash on a Lion Air flight on the same airplane model taking off from Indonesia.
Since the crashes, A.I. software called Maneuvering Characteristics Augmentation System (MCAS) has emerged as part of the cause of the crash. The Times’ report, published Saturday (June 1, 2019), provides new information about the specific overhauls to the system that made it more vulnerable to malfunctioning. It also shows how a lack of understanding between departments, inadequate pilot training on the new system, and downplaying the changes to the Federal Aviation Administration, created a perfect, deadly storm.
Boeing originally designed MCAS as an extremely limited A.I. system that would only kick in to course correct the nose of the plane when two sensors detected extreme wind resistance and force. However, in 2012, Boeing began to make changes and expand MCAS.
The public is exposed to the use of automation and AI in aviation and flight from the Hollywood movies. But, Hollywood rarely does much based upon reality or facts. they are in the fiction business. Yet, most public knowledge of AI is from these films, so the general public holds a distorted perspective about artificial intelligence. Therefore, can they actually judge the merits of AI in aviation.
As a result of these horrific accidents, the public opinion swings the proverbial pendulum of acceptance away from application towards fierce resistance and fear. But, the aircraft manufacturers will put a positive spin to AI when they are ready to relaunch it back into the marketplace. Boeing will need to do a lot of work to swing the pendulum back to the positive side again. Some suggest that they will retire the entire 737 MAX brand and rename the aircraft when they are released to place it back in service.
Would you fly on the Boeing 737 MAX? To quote Shakespeare, “A rose by any other name, would smell as sweet“.
As engineers add AI capabilities to airplanes to fly them or to help to fly them, it seems that they are still learning about these AI systems after they are in service. So, caution may be well warranted today. My preference is to have a well-trained crew to make the best decisions possible and keep my flying experiences safe.
Now, please do not misunderstand. I am a keen evangelist for technology. I love AI and all of these next generation and emerging technologies; it is just that we need prudence in the deployments. As pleased as I am in human pilots, it seems that in both of the accident’s aircraft types described here, it was human errors, corruption, and greed that had a role to play in both of these scenarios. So, maybe an AI presence to back up the human pilots is a smart move. The issue comes down to the training of the pilots to troubleshoot the AI issues in a proper and timely manner.
Human intelligence revolves around adapting to the environment using a combination of several cognitive processes. The field of artificial intelligence focuses on designing machines that can mimic human behavior. However, AI researchers are able to go as far as implementing Weak AI, but not the Strong AI. In fact, some believe that Strong AI is never possible due to the various differences between the human brain and a computer. So, at the moment, the mere ability to mimic the human behavior is considered as Artificial Intelligence.
Also, the utilization of artificial intelligence will surely make life even more convenient for humankind in the years to come and even force humans to evolve their skill sets, it will perhaps never be possible for such machines to completely replace the human resource. But then….
Educba. (2019). Artificial Intelligence vs Human Intelligence. Educba. Retrieved on October 29, 2019 from, https://www.educba.com/artificial-intelligence-vs-human-intelligence/
Kraus, R. (2019). ‘Aggressive and riskier’ A.I. — and bureaucracy — caused the Boeing crashes, report says. Mashable. Retrieved on October 29, 2019 from, https://mashable.com/article/boeing-737-max-aggressive-risky-ai/
Wikipedia. (2019). Air France flight 296. Wikipedia foundation, Inc. Retrieved on October 29, 2019 from, https://en.wikipedia.org/wiki/Air_France_Flight_296
About the Author:
Michael Martin has more than 35 years of experience in systems design for broadband networks, optical fibre, wireless, and digital communications technologies.
He is a business and technology consultant. Over the past 15 years with IBM, he has worked in the GBS Global Center of Competency for Energy and Utilities and the GTS Global Center of Excellence for Energy and Utilities. He is a founding partner and President of MICAN Communications and before that was President of Comlink Systems Limited and Ensat Broadcast Services, Inc., both divisions of Cygnal Technologies Corporation (CYN: TSX).
Martin currently serves on the Board of Directors for TeraGo Inc (TGO: TSX) and previously served on the Board of Directors for Avante Logixx Inc. (XX: TSX.V).
He has served as a Member, SCC ISO-IEC JTC 1/SC-41 – Internet of Things and related technologies, ISO – International Organization for Standardization, and as a member of the NIST SP 500-325 Fog Computing Conceptual Model, National Institute of Standards and Technology.
He served on the Board of Governors of the University of Ontario Institute of Technology (UOIT) [now OntarioTech University] and on the Board of Advisers of five different Colleges in Ontario. For 16 years he served on the Board of the Society of Motion Picture and Television Engineers (SMPTE), Toronto Section.
He holds three master’s degrees, in business (MBA), communication (MA), and education (MEd). As well, he has three undergraduate diplomas and five certifications in business, computer programming, internetworking, project management, media, photography, and communication technology. He has earned 15 badges in next generation MOOC continuous education in IoT, Cloud, AI and Cognitive systems, Blockchain, Agile, Big Data, Design Thinking, Security, and more.