For example, Enigma is a startup that allows organizations to a secure data marketplace that users can subscribe to and consume via smart contracts. Facial recognition:. However this technology would continue to grow in Facial recognition is a form of artificial intelligence application that helps in identifying a person using their digital image or patterns of their facial features.
The popular iPhoneX is already using facial recognition as a digital password. With the boom in personalizing everything — from your shopping experience to advertising, this technology is going to be used more and more for biometric identification. This will continue to rise due to the non-invasive identification and the easy of deployment. Other use cases like payment processing through security checks as well as for law enforcement in early detection and prevention of crime would be on the rise. These next-generation image recognition technologies can be used for healthcare purposes as well — to follow through clinical trials as well as medical diagnostic procedures.
Openwater , one the forerunners in imaging technologies, is pushing the boundaries of future devices that could read images from our brains! Biased data:. This topic is becoming increasingly important as machine learning models are being used for decision-making such as hiring, mortgage loans, prisoners released from parole or the type of social service benefits. Amazon is reported to have scrapped an internal hiring tool that increased bias against hiring women.
Some of these biases are conscious while some are unconscious due to data that is used for training. For example, consider a fictitious case of the decision of promoting a woman. Historical data on employment may show women getting less promoted than men and hence create discriminatory AI applications. Many more examples have led to an increased emphasis of dealing with biased data in AI applications.
As the usage of AI applications increases in , there would also be an increase in learning how to deal with biased data.
It can be argued that increased government regulations can address this issue but these regulations are often not up to speed with the technology advancements. The onus lies with the businesses to take proactive steps to adopt principles of non-discriminatory data. The World Economic Forum has released a report to prevent discriminatory outcomes in machine learning. Some of the ways this issue can be prevented is by ensuring 1. Neural networks:. To put it briefly, neural networks or artificial neural networks emulate human brain.
They store all data in a digital format — sensory, text or time and use it to classify and group the information. There is a huge demand of neural networks in robotics, to improve order fulfillment, prediction of the stock market, and diagnosis of medical problems or even to compose music! The current neural network technologies will be improved upon in This would enable this type of AI to become more sophisticated as better training methods and network architectures are developed.
This is helpful in helping autonomous vehicles or fraud detection or even to look for signs of cancer. Socio-economic models:. While AI would take away mundane jobs where there is a scarcity of resources e. Whatever is the answer, this topic is very popular and is under discussions by many governments, the United Nations and the World Economic Forum. This is because the onset of AI applications has the risk of widening skills gap and has potential to create polarized societies. While AI applications drive new skills and new jobs, it is important to complement it with value-creation.
For example, although automation might remove the need for certain jobs, there would also be a demand for high-touch jobs such as customer service representatives, teachers, caregivers etc. Some countries like Finland are even experimenting with the concept of the Universal Basic Income. Redistributive programs would continue to be the focus of attention for lawmakers and subject to debate and discussions in Deep learning:. Machine learning, the most popular form of AI algorithms, becomes challenging when the number of dimensions of data increases.
For example, calculating the price of a home given existing home prices in a location has only two dimensions of data. Imagine trying to transcribe your voice into text. The problem is now exacerbated a hundred times. Deep learning is also the technology behind self-driving cars, voice control as well as image recognition. This has increased the interest in the next generation of deep learning algorithms that can solve even tougher problems such as interpreting technology infrastructure issues.
Privacy and Policy:. The introduction of GDPR was a much-talked topic in This is important in order to protect our privacy and ensure organizations approach data privacy earnestly. Most of us are unaware of how our digital information is being used. Countries and legislators view of privacy and policy around it would continue to be of importance in The issues of consent of usage of a system, especially around AI applications would be huge given that the laws surrounding AI is still new and needs further understanding.
Countries around the world would continue to work on strategies and initiatives to guide the development of artificial intelligence AI Regulations.
As AI matures, we will need a responsive workforce, capable of adapting to new processes, systems and tools every few years. Spiritual healing : harnessing the power of prayer and focused intention to alter the health outcome for a patient. Now add a third sound source so that you can operate in three dimensions. Advances in super-learning will require the radical reformation of our learning institutions and yet will simultaneously usher in a new era of prosperity and quality of life. Time will tell. London: Associated Newspapers Limited.
Standards that are critical to ensure that safety, transparency and awareness of the complex AI technologies would also be developed. In conclusion, Artificial Intelligence is not going to see a decline any time soon. The growth of it continues as we enter and the focus would not only be on new technologies and applications in the industry but also how it intersects with the society and heralds in technology for the better.
Get started. Swathi Young Follow. This field of study is no stranger to us. Machine learning, augmented reality technologies and human-computer interface are just a few of the accomplishes in this area. If you have a smartphone, you probably spent a few minutes talking to the virtual assistant to see what it could do and what it would answer.
There you go, you have this cutting edge technology in the palm of your hand. But the future of AI has unlimited possibilities of what can be accomplished by this field of study.
And here we are again, living in the reality that only existed in movies and books a few decades ago. But the truth is we need this technology. The amount of data we are producing is increasing daily. But almost 90 percent of this data is unstructured.
To even begin to make sense and process this much data, we need a helping hand from our artificially intelligent robot friends. You know are else grows more and more every year right alongside emerging technologies? Cyber threats. Even with these improvements, companies, agencies and organizations keep getting their data stolen and violated. The firm Gemalto estimated that data breaches compromised 4. According to a recent study from the University of Maryland, hackers attack computers every 39 seconds.
We will be facing a new and improved cyber threats in hello, automated hackers tools. This is the bitter-sweet reality we live in now. The more connected we get, the more vulnerable we are. We need this technologies and their solutions to protect our personal life and our work.
We are dealing with serious threats from criminals trying to steal your credit card number from terrorists, malicious individuals, organized crime and more. Cybersecurity is the key for us to be able to take full advantage of these awesome new technologies and this connection we have with the world today without being vulnerable. You have probably heard about IoT by now. This emerging technology refers to the general concept of machines, equipment and devices that are controllable via the internet.
You can read, locate, turn something on and off using the internet, just to list a few examples. Internet of Things includes cars, wearable technologies and home appliances. Think about it this way: if a device can be turned on, it can, most likely, be connected to the internet.