Careers in Artificial Intelligence: Now More Than Ever or Just a Hoax?
Artificial Intelligence, better called AI, is probably the hottest buzzword in existence right now. But what does that even mean for you, and why should you care about the entire AI thing, which has taken the entire technological world and particularly the Silicon Valley by storm? Well, particularly it is the next big thing in the future of technology and automation. Superintelligent algorithms surely aren’t going to incinerate all jobs or wipe out humanity, but software has gotten significantly smarter as of late, with them doing everything from medical diagnostics to serving up ads. Much as it would destroy tons of jobs, but it will create tons too. In fact, some people believe AI is over hyped. Regardless, it is also incredibly important.
So, what exactly is Artificial Intelligence?
The official idea and the definition of AI was first coined by John McCarthy in 1955. According to him, “Every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it. An attempt will be made to find how to make machines use language m form abstractions and concepts, solve kinds of problems now reserved for humans, and improve themselves.”
In essence, AI is a machine with the ability to solve problems that are innately done by us humans with our natural intelligence. A computer would demonstrate a form of intelligence when it learns how to improve itself at solving these problems. Basically, improvisation.
The primary aspects upon which AI prevails include:
1. Simulating higher functions of the human brain.
2. Programming a computer to use general language.
3. Arranging hypothetical neurons in a manner so that they can form concepts.
4. A way to determine and measure problem complexity.
5. Self-improvement.
6. Abstraction: Defined as the quality of dealing with ideas rather than events.
7. Randomness and creativity.
At present, we’ve looked into language, measure of problem complexity and Self-improvement realistically to some degree. It is very recently that we’ve started looking into randomness and creativity, and that is where the entire idea of making a career in AI comes. Creativity and inventiveness to solve real world complex problems with the help of AI that would otherwise be difficult for humans.
Let us look into “intelligence” now, as this seems to be the central object on which AI persists on. Some of the most important factors of intelligence include:
I. Generalisation Learning: Learning that enables the learner to perform better in situations not previously encountered. The most important example of this would be Machine Learning and NLP.
II. Reasoning: To reason is to draw conclusion(s) appropriate to the situation in hand. E.g. programming robots to give way to humans, self-driving vehicles giving way to ambulances etc.
III. Problem Solving: Pretty self-explanatory. Find x, given such and such data with such and such constraints.
IV. Perception: Analyzing a scanned environment and analyzing features and relationships between objects. E.g. self-driving cars.
V. Language Understanding: The primary methodology through which humans would interact to AI and teach it stuff. AI follows syntax's and other roles similar to a human.
These are the primary factors which are to be kept in mind while working with AI.
Some of the most popular examples of AI in the present scenario include Machine Learning, Computer Vision, Neuro-Linguistic Programming, Robotics, Pattern Recognition, and Knowledge Management.
AI is definitely the future, no doubt about it. And the career prospects it puts forward are even more lucrative and challenge the creativity and inventiveness of the individual. We’ll be talking about Machine Learning, a subsidiary of Artificial Intelligence which has an extremely high demand in the tech industry these days.
Machine Learning
Machine Learning refers to algorithms that enable software to improve its performance overtime as it obtains more data. This is programming by input-output examples rather than just coding. For example a programmer would have
no idea how to program a computer to recognize a dog but he can create a program with a form of intelligence that can learn to do so. If he gives the program enough image data in the form of dogs and let it process and learn, when you give the program an image of a new dog that it’s never seen before, it would be able to tell it’s a dog with relative ease. THAT, is Machine Learning. Giving the machine input and let it process and learn.
Career Prospects in AI and Machine Learning(M.L.)
According to an Oxford University analysis, close to half of all jobs will be taken over by robots in the next 25 years. But not everyone is alarmed about the prospect of radical change in the labour market. In fact, the consultancy service Cognizant notes that while creation destruction has always been with us, so has re-invention. Sure, AI would take away jobs, but it would also create new ones.
1. Data Scientist: Data Analytics is currently in great demand. Now data scientists, obviously, work with data. This involves plenty of activities such as sampling and pre-processing of data, model estimation and post-processing. Technical Prowess in R, Python etc. is also crucial. AI employment is important on an incremental scale as data scientist job requires creativity for repetitive processes.
2. Cyber City Analyst: Smart cities are already being built in major parts of the world. When they’re up and running, cyber city analysts will keep the tech underlying the magic in good repair, much like telephone linemen. “Cyber city analysts ensure the steady flow of ‘healthy’ data around our cities — including bio data, citizen data, and asset data — by ensuring all technical and transmission equipment functions without being compromised,” says Cognizant.
3. AI Assisted Health Care Technician: This is essentially nursing updated. You’ll be requiring the same health care skills but also the tech savvy to deliver them remotely, using telemedicine tools and in-home testing equipment. Using AI, nurses would be able to diagnose and treat more ailments, leaving doctors to support these technicians and handle trickier cases directly. 4. Quantum machine-learning analyst: The most tech-centric of all the jobs imagined, this one is suitable for only the most highly skilled applicants. “Individuals in this role research and develop next-generation solutions by integrating the disciplines of quantum information processing with machine learning,” according to prospect employers of this profile.
5. Financial Wellness Coaches: Keeping track of finances is going to be
even more trickier when cash will be obsolete and bitcoin would be the
new norm, and automated loans and micro-payments will be
commonplace. In the face of increasingly digital finance transactions,
many banking customers are too time-crunched to fully understand fee
structures and optimal approaches to financial management. The solution
will be financial wellness coaches.
6. Precision Medicine: Genetics and genomics look for mutations and links
to disease from the information in DNA. With the help of AI, body scans
can spot cancer and vascular diseases early and predict the health issues
people might face based on their genetics. Career prospect for the
development and consecutive updating of such software.
7. Health Monitoring Trackers: Wearable health trackers — like those
from FitBit, Apple, Garmin and others — monitors heart rate and activity
levels. They can send alerts to the user to get more exercise and can share
this information to doctors (and AI systems) for additional data points on
the needs and habits of patients. Prospect to apply machine learning in
analyzing data among millions of people.
8. Digital Consultation: Apps like Babylon in the UK use AI to give
medical consultation based on personal medical history and common
medical knowledge. Users report their symptoms into the app, which uses
speech recognition to compare against a database of illnesses. Babylon
then offers a recommended action, taking into account the user’s medical
history. Prospect for development of such apps which use speech
recognition, accelerometer and other sensors to measure symptom
seriousness with respect to a particular illness.
9. R&D Scientist in AI: This is probably the most important aspect of AI
development is its persistent research to further better it. Take for
example Google Duplex which uses predictive data and Machine
Learning to place calls for the owner of the device to another human to
place appointments etc. Google Lens uses ML to recognize real world
objects and search for them on Wikipedia or Amazon. The possibilities
are virtually endless with ML in the field of AI.