Artificial intelligence (AI) is one of the newest yet fastest developing technology, but its possibilities still remain unclear to some people. While there is no prediction engine that can plot the future course of AI, but we can fairly certain and predict about what might happen in the near future.
1. Healthcare more accurate and less costly
AI would surely reduce the cost for healthcare, as most of the current procedures could be automated using AI while also customizable. For example, it could be automated reporting, automatic equipment setting initialization, or optimized scheduling for patients and staff. Whereas for customization, it could be done for accurately enhancing staff and patient experience, and reducing the cost at the same time.
Besides that, AI has the ability to acquire data from multiple hospital information flows and databases, more importantly it could be done in real-time. By doing so, electronic health records, emergency department admissions, equipment utilization, or even staffing levels could be used to interpret and analyze for methods to enhance care efficiency and capabilities.
2. More devices will run AI-powered technology
AI will become more accessible as the expertise, software, and hardware required for deploying AI become cheaper and more available, hence we would start to see it used in more tools, gadgets, and devices. Currently, we already see AI in powering forecast or prediction in our personal devices which includes phones, computers, and watches. As the cost of having a system incorporated with AI is reducing, we could predict AI to increasingly be embedded into our vehicles, household appliances, and workplaces tools. Together with technology such as virtual and augmented reality, and internet related like cloud and IoT, we might have more and more devices of every shape and size that capable to learn or even think for themselves.
3. Increased human and AI cooperation
More and more of us are getting used to the idea of working alongside AI-powered tools and bots in our daily and working lives. Although AI currently yet to be able to implement into areas that require imaginative, communication skills, design or strategy, hence such areas still require our human skills, but there will be tools built that allow us to make most out of our skills. Whereas for people who have to handle a lot of data or company that deals with robot, they would have to look out for this as AI might augment humans with their analytic abilities. AI have strong analytics ability, it is fed by massive datasets, and it is also updated in real-time. From there, humans can learn various new skills alongside the software-based and robotic tools. As an example, we could see many chat bots being developed that not only function as a digital entities, but also personified into a robot that supplements a human worker, and also installed with sophisticated actuators and sensors that enable it to interact more smoothly with human.
4. Unknowing interaction with AI
Despite of huge investment in the past in natural language powered chatbots in customer service, most of us can still recognize if it is a robot or a human that we are dealing with, but this might soon be changing. It is now becoming a trend that the datasets for training natural language processing (NLP) is becoming more available as it is becoming more popular, and this will make the chatbots to be more human-like and we might have difficulty sometimes in distinguishing between machines and humans.
Other than that, more and more deep learning models are moving towards new direction of semi-supervised learning which is the reinforcement learning, whereby the AI will be taking the more suitable action to maximize reward according to its situation. As the result, such algorithms would try to match the speech patterns from the current human language, and it might trick us into believing that the other end is a human.
5. AI can identify us even when we don’t
This might be an unsettling scenario for some people, but the technology of facial recognition is only going to be more and more advanced as we move into the next decade. Although it is now known to almost everyone that China national government has implemented facial recognition as compulsory for accessing services like communication networks and public transport, but in other part of the world actually we are also under monitoring of facial recognition, for instance Amazon Go stores that function cashless and with absence of in-store workers.
Besides that, not just China but other countries also having governments and corporations that are investing more and more into facial and human recognition algorithms that could tell who we are, and also recording our behaviors, daily lifestyles, and activities. Amazon is now actively advertising its face recognition service, it is a cloud-based AI known as Rekognition, and various law enforcement agencies have already adopted it, as it could identify up to 100 individuals in a single image, and face match could be done using its databases comprising of millions of faces.
6. AI become less data-hungry
The AI currently are majority based on deep learning techniques, and hence they are data-hungry, meaning that the algorithms built can only work accurately when it was trained and validated on massive amounts of data, but not all kinds of data are easy to collect or made available to everyone, hence some AI developing companies would find it challenging in getting the correct kinds and necessary volumes of data. Many researchers in the AI field are now beginning to test in synthesizing methodologies that could overcome the limitations of real-world data, and making the synthesized data available to them.
One of the most data-hungry industries currently would be the automotive industry, as there is a need to understand the things that happen to the people inside of a vehicle, as the industry is moving to develop advanced driver safety features and to personalize the transportation experience. However, it is very difficult while also time-consuming and expensive to collect real-world driver data. Hence, data synthesis could address this problem, and the automotive industry could benefit from it, such as using video of a person driving the car to create new scenarios for the AI.
Futhermore, advances in AI areas such as generative adversarial networks (GAN) has enabled many AI research to synthesize their own training data. However, this does not mean that the need for collecting real-world data could be eliminated, as the real-world data are always critical to the development of accurate AI algorithms, while synthesized data might just augment the datasets.
7. AI in cybersecurity
Hacking, phishing and social engineering attacks are becoming more and more sophisticated as they are powered by AI and advanced prediction algorithms, hence smart technology play an important role in protecting us from these attempted intrusions into our lives and privacy. AI could be trained according to some specific digital pattern, so that it could be used to spot the giveaway signs from digital activity or transactions as it follow patterns that are likely to be indicators of nefarious activity, and raise alarms before the breaching of network defenses or compromising of sensitive data.
The capability of AI in cybersecurity will be further maximized as 5G and other superfast wireless communications technology are being developed and businesses could have new and huge opportunities, whereby they could provide services in new and innovative ways, but this also means that they will also potentially open up to more cyber-attacks. Hence, spending on cybersecurity will continue to increase, and those with relevant skills will be highly sought-after.
8. Area of deepfaking
In the previous years we could witness that numerous deepfakes that went viral especially on social media networks. Deepfakes are videos that hard to be distinguished from the real video, such videos could be catastrophic as it can spread opinionated disinformation, cyberbullying, corporate sabotage, and so on. But with new developments and trends in AI, it will be much easier to detect if it is a deepfake video.
