It’s no surprise that knowing whatever we do or search on the internet goes straight to the data pool. The facts that we quote or the numbers that we bring up for estimation are nothing but a form of data or a set of information. The recent reports from IBM cloud reveal that 90% of all the global data produced dates back to the last two years.
The data pool is growing day by day at an astounding pace. In the year 2020, 1.7 megabytes of data was produced for everyone living on the planet. Multiplying these 1.7megabytes with the total world population will be too much to handle, but this is how fast we generate data.
Today’s generation has grown up in an environment where they haven’t spent a single day without the internet. Their digital footprint has a more profound impact than those who got acquainted with the internet in their early youth or old age, like baby boomers.
The innovations in technology, communication, and social media have piloted interconnectivity in our society. We have more information available today than we did before. Businesses, communication, news, and entertainment have gone digital. Every industry relies on the data they have to project their future goals. The events around us and their impact on our lives contribute to the events that are yet to happen.
The year 2020 was full of struggle, and the world endured many hardships and innovations to suffice the need of the hour. Businesses and other industries shifted their workforce online, while the healthcare industry also experienced the benefits of telehealth and online treatment facilities. From working on-premises to working online, things took a turn. This article will highlight significant data science predictions set to reshape and reform business and other operations worldwide.
- Skyrocketing AI investments
The concept of artificial intelligence is not new, but the world witnessed the rapid growth of AI in the year 2020. The resulting digital transformation forced upon companies and individuals opened career pathways for education centered around data science like an online masters in data science to help extract information and project future predictions.
Also, it accelerated the usage and development of artificial intelligence. Like Gartner once predicted that every business, small or large, will need a website to survive in 2000, the same goes for AI in the year 2021. Incorporating artificial intelligence in business operations has given business owners the liberty to enjoy a more effective and aligned execution of a task with minimal human resources.
The ongoing pandemic has forced many individuals to work from home and businesses to work with fewer workers; AI has facilitated many companies in customer services. Many companies will use AI for making business decisions, significant cost savings, and increased productivity.
- Man-machine and workplace AI collaboration
During the pandemic, many companies and employers had to cut down their staff and fill the gap; they shifted to automated procedures; workplace AI has been a long-standing trend. The pandemic has boosted its emergence due to a significant digital transformation.
The post-COVID-19 world is more virtual and touch-less. Industries like retail, hospitality, food, and beverage will be relying more on man-machine and AI collaboration to automate their operations and processes while ensuring the safety of human beings in a post-pandemic world.
The increasing demand for AI is reducing the talent pool. Businesses rely more on AI service platforms to boost their business productivity and performance to build their solutions.
- Developing model monitoring solutions
Many businesses depend on AI and machine learning. The global pandemic affected every facet of industries worldwide. Organizations relying on AI and ML for the automation of their operations and decisions became vulnerable.
The digital transformation brought along many challenges, and one of them is the primary data drift. A significant change in model input has led to performance degradation and inaccuracy of the outputs.
The massive data drift has occurred due to large-scale changes in human behavior since the beginning of the pandemic. Businesses can only plan or project their future goals if they can control these changes, which is why many companies are focusing on developing or invest in robust model monitor solutions.
- Advancements in federated learning
Online privacy and security have become mainstream topics after several high-profile cases and documentaries. As much as we are relying on data, hacking or cyber-attacks are also inevitable. Ensuring data privacy is essential, and federated learning enables mobile phones to learn a shared prediction model.
Doing so will keep the device’s training data instead of uploading and storing the data on the cloud or any other central server. Organizations like hospitals that operate under strict privacy constraints can benefit from federated learning, ensuring their data privacy even when there is no internet connectivity.
- Increase in deep fakes
With increasing volumes of data, the increase in deep fake data is also on the rise. Deep fakes involve both punishing production and distribution, and they will also perturb AI training. Synthetic data is easy to mold, and people may use it to release misleading information.
Creating rumors and publishing misleading information through deep fakes means that non-tech-savvy people can easily go astray believing the deep fakes are indeed real. However, many companies are now using detection software to identify the deep fakes using their names and spreading fake information. These deep fakes can be in audio or videos and may pose a threat to AI apps.
Conclusion
Glancing at the post-COVID world, we can see the changed normal and industrial operations becoming more virtual and touchless. The computer vision technology and model monitor solutions are making their way to the frontline to streamline the performance assessment of remote workers.
With increasing man-machine and AI collaboration, industries will enjoy services provided by AI without hiring humans. This will save the cost of training human talent, and Data scientists will use these predictive analytics to extract data and use current information to project future changes with precision.
With AI taking over every aspect of our lives, consumers’ understanding of technology will also see a massive change in the upcoming years.
