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There was a time when Artificial Intelligence (AI) was often portrayed as robots. Machines that exhibited human-like characteristics (learning and decision making) with an artificial brain. Today, AI encompasses anything and everything. Be it vehicles, entertainment, corporations, smart homes, google search algorithms, education, law, or medical services, AI has transformed all the sectors for the better.
Until today, artificial intelligence has outperformed humans in specific tasks. To quote a few examples-
The worldwide AI market is expected to grow by $120 billion by the end of 2025. The AI software market, on the other hand, is expected to touch $22.6 billion in the year 2020, says TechJury.
Now, researchers and technologists are all set to build artificial intelligence that would outperform humans in every cognitive task. Therefore, machine learning and deep learning are essential aspects of AI; deep learning being the latest breakthrough. It has left no stone unturned in the application, whether it is our personal, professional, or social life.
And AI-powered education seems like a great substitute for a better future.
The growing popularity of AI is both the cause and consequence for tech giants and businesses investing heavily in it. Intelligent and profitable digital transformation has now transformed our industries. Moreover, fascinating controversies and myths around the future of AI also continue to trigger the curiosity in humans.
The question is what drives intelligence and why is it important for us to know that?
Well, the major role of AI is to make accurate predictions after learning from consumer activities. This connects us back to AI machine learning and deep learning. Every possible data input contributes to the process of decision making. AI algorithms generate business analytics based on different types of annotated data. So, data is the lifeblood of AI. A vast pool of "data" from multiple sources drives this intelligence. This is also known as the "Big Data pool".
No wonder why AI and Big Data are now seemingly inseparable!
It is no secret that AI or Machine learning models work on a large proportion of training data. Just like humans, machines, and algorithms also learn with rigorous training. But the process of data input isn't as straightforward as in humans. This indicates how data annotation is important for thriving in the AI world.
Labeling the content of various forms i.e., text, speech, or multimedia, making it discernable to machines is called data annotation. Now that the world is going through a paradigm shift. All the AI and ML companies require large volumes of annotated data for training their ML models. This indicates the urgent need for skilled data annotators. The skill is all about enhancing customer experience through advanced data annotation techniques.
Data annotation is a critical factor in ensuring that our AI and machine learning projects scale. Even the most technically advanced algorithm is not applicable without data. Data annotation gives us a leg up on the machines as we are responsible for identifying annotating data to the machine. Certain sources reveal how in present-day AI projects, 80% of total project time is spent in data preparation and even the slightest of errors can cause huge damage. Providing machines and algorithms, that access to learnable data is the biggest competitive advantage and will remain so for years to come. This is a reason enough to claim that data annotation is a prospect career and is yet to thrive.
This makes us wonder what are the different types of data annotations and their implications.
Here's the answer-
1) Text Annotation
Text annotation is employed for Natural Language processing by machines. AI virtual assistants and chatbots are common applications of text annotation. There are many sub-categories of text annotation, based on different applications.
2) Audio annotation
It is similar to text annotation with the only difference to make Natural Language processing for "speech", to make it understandable to the machines. In other words, the time-stamping of speech data and transcription for clear identification of pronunciation, modulation, and language is a part of this process.
3) Image annotation
For applications including face recognition, computer/robot vision, the ML model should be able to interpret images or objects. This annotation finds common applications in healthcare services and smart devices.
4) Video annotation
Video annotation, as the name suggests is done to make movement recognizable to machines. For example, video annotation is used to train the visual perception in autonomous vehicles.
The virus has accelerated the trend that was already underway. The global e-learning market was already booming in the last few months. This significantly high growth of adoption is indicated by how global tech investments reached US$18.66 billion in 2019, as indicated in the World Economic Forum.
The student community is also amongst many "hard-hit sections of the pandemic". As schools and universities close, remote learning emerged as a new normal. Over 1.2 billion students across 186 countries are affected by school closures.
Guess what?
According to the World Economic Forum, report, the overall market for online education is projected to reach $350 Billion by 2025. Thanks to the pandemic. Whether it is online learning software/apps like Coursera, virtual tutoring, language apps, or video conferencing tools as zoom and Google meets, there has been a significant, in usage since COVID-19. Many virtual education platforms, for example, "Byjus" have offered free access to students in response to their high demand. Some other platforms like the Singapore based "Lark" have ramped up their global infrastructure to offer one-stop facilities to teachers and students for effective e-learning experience. But, this unplanned rapid shift towards online education, with hardly any preparation and insufficient bandwidth, will only be unconducive for growth. For this, we rely on AI. It will transform education for better user experience and effective learning.
While social, economic disturbances continue to exist in the pandemic, adaptive learning technologies have the power to orchestrate students towards their careers. The first and foremost challenge lies in providing equal importunity for all students to access live classes, course material, and abundant online learning platforms. Many students (the figures vary across different countries) struggle to participate in digital learning due to unreliable internet connection. There is a significant gap between those who come from privileged backgrounds and those who come from disadvantaged backgrounds.
Secondly, the platform changes, learning, and teaching styles also change. Now that the traditional classes are shut, the world needs to think of sustainable teaching and learning strategies to entrust students with education. Mere telepresence without regulation and adaptability won't yield much. A controlled yet the unrestricted environment is a must for a fruitful learning experience. And "Adaptive learning" seems like the best antidote.
What is adaptive learning?
Just the one where course material is available online?
Well, that would be an incomplete answer. Adaptive learning is not just about online courses or automated quizzes. It is a broader term that encompasses performance tracking through continuous assessment and immediate and personalized feedback. It is almost like a course material personalized to students' learning techniques and pace.
Online learning, although, seems more effective if students have access to the right technology. Yet, a structured environment is needed to ensure the effectiveness of online learning. We need to think beyond just replicating the physical classrooms via online video lectures. Intelligent tools for collaboration and student engagement are a rescue for making the trend last longer!
Another important concern is how our institutes should think beyond just not learning and focus more on "critical thinking" and "adaptability". The current transition to online education is definitely not a hindrance, rather the first-hand experience to learn these skills.
Besides all the tools that we use today, here's how AI-powered education will make online learning sustainable
1) Auto grading for correctness and promptness
In a traditional academic set up, most of the teacher's time is consumed in grading the assignments and classwork of their students. What if this could be changed?
With auto-grading through AI and ML algorithms, we can foster better time utilization. This will allow teachers to teach their students effectively and will also ensure fair grading based on performance.
2) Asynchronous learning sessions with AI
Millions of students are studying from home and sometimes it becomes difficult for students to attend synchronous classes right in the time. However online learning, unlike traditional classroom learning, does not allow re-reading, skipping, or learning at students' own pace. AI technology can be employed to offer personalized instructions to students who are unable to attend or follow live sessions with teachers. AI-powered software like "Amira" is aiding students to transition from conventional classroom learning to remote learning for upgrading their skills. TechKit is another such platform that promotes online skill and career development for students through personalized learning assurance.
3) Performance tracking with AI
Adaptive learning technologies can extensively track student performance. Students who are not able to catch up during online classes also have a fair chance to learn and grow. Above all, they can be adaptively involved in extended lesson related activities until they are readied to advance. Gaps between the lectures and instructional material often lead students confused. The best solution for this problem is to engage in personalized and feedback-driven conversations in the form of chatbots. The learning process is continuous and students get to control their learning patterns.
4) Learning from smart content
Books seem old school to students these days.
But what if the books were presented to students as flashcards, practice tests, self-assessments, simulations games, and interactive summaries?
Well, distributing smart content is a tough job. However, AI-powered interfaces make it easy and effective. To quote an example, JustThatFacts101 is working towards the common goal of facilitating "efficient learning" in students.
We have comprehended by now, there are many creative ways to impart theoretical education to students across continents. Artificial intelligence will complement our existing approaches to make it more competitive in the years to come.
But have you ever thought about how important it is to provide skill development training and practical education to children?
Well, it is essential because skills, in addition to knowledge, will land our students into their dream careers. And this job is done just right through boot camps!
What is the main difference between a boot camp and an online learning course?
If you have this question in your mind, then you are on the right track!
Although these may sound similar yet boot camps are quite different in implementation as compared to classes or courses. Boot camp, whether online or on-site, are designed to make you a trained designer or professional in a matter of a few weeks. Regardless of the mode of education, a student is navigated through the entire course and practical training sessions by the assigned mentor. It offers various advantages over a self-paced course or online learning lessons in the following ways-
Online Bootcamps are an innovative way of imparting (practical) technical education to young adults. The web development market is expanding like the universe. In other words, having a valid knowledge base and skillset can land capable candidates into decent jobs in the tech industry. Learning varies from student to student. Hence, for any learning experience to be fruitful, it is important to understand students' needs and offer them personalized coaching for effective learning.
So, the key ingredients for success in a technical career are- personalized mentorship, real-time training, and scholarships. With boot camps, students get an opportunity to learn the required skills while being in the comfort of their homes.
"What else can one expect, if AI-powered online education enabled us to secure AI- empowering jobs!"
Online platforms like Techkit are offering affordable online boot camps to students,and blue collar workers with a vision of connecting capable students,and workers to the right employers and help them build their career .Students, even with zero knowledge about AI, can take advantage of such platforms to become fully trained professionals in limited time. The course design also includes comprehensive career development services that ensure employment to young, and capable professionals. What else, in the digital era, can one ask for!
We may want to believe that softwares won't replace teachers. But AI-powered education interfaces can assist teachers with their jobs and make it more productive. The ongoing trend is here to stay! The pandemic is an opportunity for us to experiment and deploy new technologies to make education, meaningful and delightful experience for learners. The transformation is for real and AI has the capacity to make it ideal. At least in this regard, AI will just empower.
Lavpreet Kaur is an engineer with vivid research experience in telecommunication and Wireless Sensor Networks. Currently pursuing Masters in Mass Communication & Journalism. A professional Blogger and content creator with a diverse experience of more than 2 years. Young educator, public speaker, youth leader, and social activist actively working with various national and global organizations. Recognized as the best student by the Indian Society of Technical Education for overall excellence and honored at various National and International conferences.
Designation: Content Writer
Website: https://www.techkit.org/
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