Areas of Accelerated Machine Learning Adaptation Post-COVID -19 Crisis
As we are witnessing expansion of corona-virus pandemic across the world, businesses are running in to chaos. We all are experiencing such scale pandemic first time in our life time, no business would have planned earlier to deal with this kind of crisis. Here in this article I will be providing my thoughts on areas, which are going to see wide scale Machine Learning adaptation post this crisis :
1. Healthcare digitization & technological advancement :
The Healthcare industry is going to see the biggest technological advancement post this COVID crisis. A huge amount of data will be available in digital form now. Healthcare providers and patients will see the power of digital consultation. In countries like India, now most of the major hospitals are providing digital consultation to assure the right candidates are coming for further clinical assessment.
Availability of quality historical data is always the biggest challenge in the healthcare industry to apply machine learning algorithms. Now all data is getting recorded in digital form i.e. consultation, prescription, online test booking, home sample collection, online report generation. This will all be linked to a single patient's unique profile. This data (in anonymous form) will be very helpful to develop an umbrella of ML solutions at each patient level.
In addition, Stanford is conduction a virtual conference titled “ Covid 19 and AI” on 1st April 2020, where top researchers are joining. All this is open to the whole world. As all smart brains across the globe will be looking to solve these complex healthcare challenges, which in turn will revolutionize the adaptation of AI technology in the healthcare area, Along with that, Google has recently published a paper providing a detailed survey of applied machine learning in scientific discovery.
2. Long term impact on Consumer Behavior :
First time in human history such a large number of consumers across the globe are using technology to fulfill their survival needs. Many of them going to realize the value of technology in their daily life. This is going to change their purchase behavior later. Many of the machine learning models (build on earlier consumer behavior) which are not auto-retrained, will see a drift in their prediction accuracy. This will mandate large-scale adaptation of auto retraining in machine learning, concepts like AutoML, MLOps will be useful across organizations.
3. Online Education :
I am amazed to see that how kids are attending classes online, doing assignments and teachers are taking virtual classes. Online education is gaining momentum each day, as result, we are seeing an ocean of courses available for each skill, age group. Now post this crisis, we will see a huge shift towards online education from all age groups. For example, already companies like Slack, Zoom are gaining momentum recently, read this.
As I said earlier, we have umpteen courses available to select for each skill on platforms like i.e. Coursera, Udemy, Udacity, Khan Academy, YouTube Channels, LinkedIn Learning, and so on. Some courses are good for beginners and others are for varied experience people. Personalized courses suggestion will be another area where machine learning will see the wide-scale adaptation.
4. Cybersecurity :
As most of the population across the globe is working from home, organizations will require to accept this reality going forward. This will make organizations/personal data more vulnerable to threats due to exposure of outside networks, a variety of applications, and devices, read this.
Machine learning could be useful to detect any anomalous usage of data to avoid any data-related security challenge.
5. E-commerce Expansion :
E commerce is already gaining traction year over year like many large enterprises are having plans to offer products on eCommerce platforms. With this mandate of social distancing, we will observe an acceleration of adaptation of e-commerce across enterprises. Small shop owners also need to develop mobile applications or become part of some larger platform to ease the delivery of their products.
We all know how heavily e-commerce giants are using machine learning ranging from recommendation engines, pricing engines, personalized marketing, etc. We will see an adaptation of this across industry segments, even small mom-and-pop stores using mobile applications for delivery will try to exploit machine learning.
6. Cloud Adaptation :
As most of the companies are now experimenting complete employee base working from home across geographies. Need will arise for software development without enterprise infrastructure availability. We will see a widespread adaptation of the cloud from small to large organizations. This will also increase the development of machine learning algorithms on the cloud, along with the movement of working enterprise deployments of ML models to the cloud.
7. Energy optimization :
With the large population on the planet is staying home, energy consumption is going to increase. Many companies are already out there in this area to provide applications-based real-time user insights to reduce energy consumption. However, with this crisis, larger consumers are going to realize the value of machine learning-based insights to optimize their home energy usage.
These are the few thoughts I have, however, I am open to suggestions and new ideas from everyone around here. #StayHomeStaySafe
