Rounak Jain Jan 30, 2020 1 Comment
It was the year 1956 when the term “artificial intelligence” was first coined by John McCarthy. A demo of the AI program at Carnegie Mellon University was also attempted. More than half a century later, we see AI making a massive impact on our lives. From Siri to driverless cars to International Space Station, Artificial Intelligence has made its proud presence everywhere. Though this technology is still improving, the last decade was a lot about Artificial Intelligence and many companies worldwide tried their hand on it. They did reap its benefits and now close to 40% of businesses use artificial intelligence (AI). As we enter into a new decade, let us see what are some major trends of Artificial Intelligence to watch out for in 2020.
Machine Learning and AI technology are being implemented in phishing and hacking cyber-attacks around the globe these days. This has rendered conventional cybersecurity ineffective in detecting these cyber threats. The potential cybersecurity problem rises manifolds as an estimate suggests that by 2020 there will be around 24 billion devices connected to the internet. Simultaneously, this calls for the usage of AI technology in predicting and managing these malicious attacks as well. Big cybersecurity firms have started using AI for pattern recognition to detect viruses and malware. 75% of the surveyed executives also believe that AI allows for a faster response to security breaches. It now is a battle of whose AI is better, the one who attacks or the one who defends.
An Allied Market Research study indicates the global AI health care market will likely reach $22.8 billion by 2023 and help solve many existing problems. For example, Artificial Intelligence has the potential to solve the “iron triangle” of healthcare’s three interlocking factors viz. access, affordability, and effectiveness which often require negative trade-offs. With AI, we can cut costs, improve treatments and bolster accessibility in sync. Another way to slash costs is to transfer time-consuming labor-intensive human tasks to machines and allowing patients to perform self-service for their care needs.
Additionally, Artificial Intelligence can acquire real-time data from multiple hospital health records, emergency department admissions, equipment utilization, staffing levels, etc. and to interpret and analyze it in meaningful ways. This will enable a wide range of efficiency and care enhancing capabilities in the form of optimized scheduling, automated reporting, and automatic initialization of equipment settings.
One of the game changers in terms of utilizing AI in the drug discovery area is the speed to market from a cost and time perspective. For example, accelerating molecule discoveries or identifying compounds. Another emerging Artificial Intelligence trend is that of data sharing. Machine Learning relies heavily on data to learn and perform some prediction or analytics. There are several data-sharing consortium and programs developed which are sharing data across for the greater good. For example, The Machine Learning for Pharmaceutical Discovery and Synthesis Consortium at the Massachusetts Institute of Technology (MIT), is a data-sharing program that includes companies such as GlaxoSmithKline (GSK), AstraZeneca and Eli Lilly. Their progress includes automating molecule design to speed up drug development. AI will continue to play a vital role in drug discovery and put to use for the greater good of mankind.
2020 can be the year when the manufacturing industry embraces AI to modernize the production line. One of the major challenges in the industry is quality control. Product managers are struggling to inspect each product and component while also meeting deadlines for massive orders. By integrating AI solutions as a part of workflows, AI will be able to augment and address this challenge. AI will also augment existing processes in the manufacturing industry by reducing the burden of mundane and potentially dangerous tasks. It will also free up workers’ time to focus on innovative product development that will push the industry forward.
A lot of research is going on to automate AI. The idea is to automate steps in the life cycle of AI models to help scale AI more widely into the enterprise. To share some examples, we already have Google’s AutoML, a tool that simplifies the process of creating machine learning models and makes the technology accessible to a wider audience. Last year, IBM launched AutoAI, a platform for automating data preparation, model development, feature engineering, and hyperparameter optimization. This will help spread wide and enable easy usage of Artificial Intelligence to the masses.
Deepfakes (a portmanteau of “deep learning” and “fake”) are a branch of synthetic media in which a person in an existing image or video is replaced with someone else’s likeness using artificial neural networks. They often combine and superimpose existing media onto source media using machine learning techniques known as autoencoders and generative adversarial networks (GANs).
We can manipulate videos and images by using Adobe Photoshop or other software etc. It is a time consuming and tedious process. Artificial Intelligence is making the process of generating fake videos fast and cheap. Deepfake videos are turning out to be a source of worry as it is being used to spread political misinformation and propaganda. Additionally, celebrities are also vulnerable in the light of deep fake videos. It is worth noting that there exist ways and tools to detect these deepfake media as well. Google and Facebook have been performing heavy research in this area. It will be interesting to see if such tools evolve faster than the technology generating fake videos or deepfakes will become more troublesome.
In the last few years, we saw an increased presence of chatbots. Even though they use Natural Language Processing, we can quickly identify if we are interacting with a bot based on the conversation. That will change. These bots are repeatedly learning and improving owing to the Deep Learning and reinforced Learning technologies. Very soon it might so happen that we do not even recognize we are indeed communicating with a bot for assistance or information.
One of the biometric authentications in vogue is facial recognition. Many new smartphones sell this as a phone unlocking feature. The major usage of this technology is in surveillance and marketing. Airports like Los Angeles and many other uses this technology for travelers’ identification. According to a research report “Facial Recognition Market” by Component, the facial recognition industry is expected to grow to $7.0 billion by 2024 in the U.S. However, there are problems with its accuracy for which people are raising concerns. San Francisco banned the use of facial recognition software by the police and other agencies. Nonetheless, this technology is improving and is here to stay and grow.
“With greater power comes greater responsibilities”. AI indeed empowers us all in many ways. But with that comes responsible usage of the technology as well. AI ethics is a growing focus. Last year, the European Commission published a set of seven guidelines for developing ethical AI. Even the global giants Google and Microsoft have taken steps toward making their AI development conformant to ethical norms.
There are some failures of AI noted recently, such as Apple Pay rollout, or the surge in interest regarding the Cambridge Analytica scandal. It becomes a concern that the developers create and use their creations within an ethical framework. Also, create a demarcation as to what AI should be or should not be used for.
These are the top 10 Artificial Intelligence trends which we think will gain more popularity and improve in 2020. What are some trends you think should be on the list.? Do comment.