Leveraging Machine Learning To Design Better UX
Machine Learning is the most sought after topic in the field of software Industry and would be considered the most in-demand technical skill going ahead. A Machine Learning algorithm analyze historical data, build models & predict outcomes. Machine Learning has got vast industry transformation capabilities and is used across sectors for business efficiency. Over the years it has been widely used for image & face recognition, it is also used in the e-commerce domain in the form of recommendation engines. Through item-item collaborative filtering algorithm Amazon recommends programming titles to a software engineer and baby toys to a new mother. ML is also used for cyber security, public safety & healthcare domain.
What is machine learning?
A machine learning algorithm identifies patterns in the data that deliver insights and increase the chance of better predictions and decision making. There are different types of
The point of supervised, machine learning is to fabricate a predictive model based on the input and output data. A supervised learning algorithm takes a known set of input data with a labeled output. Let’s say you want to classify images into 2 categories male & female, you train the machine with a set of labeled images and build a model when a new image is shown to the model as an input the machine can classify the image and put them under respective category. Classification and regression techniques are used to develop predictive models in supervised learning.
Figure 1. Supervised Learning
Unsupervised learning finds hidden patterns or intrinsic structures in data where the input data are without labeled response. We take the earlier examples of images, and this time there is no labeled information the machine tries to make a sense of the images to draw an inference. Clustering is the most common unsupervised learning technique.
Reinforcement learning is a trial & error learning where the reinforcement agent learns from the consequences of its actions. Take the example of how a dog is trained. If the dog follows instruction and obeys we encourage by giving biscuits, if they don’t we punish by scolding. In the same way, if the system works well a positive value is given (i.e. reward) if not a negative value is given (i.e. punishment). The system which gets punishment improves by a trial & error method .
Usage of Machine learning
Machine Learning has the ability to identify patterns that humans tend to overlook. Machine learning has earned a substantial spot in the core territory of user experience, however, its contextual usage often gets unnoticed. Amazon uses a machine learning algorithm that will “learn which reviews are most helpful to customers” — that is, which reviews are real and which ones are fake . DeepText an unsupervised machine learning algorithm is used by Facebook interpret the meaning of posts and comments . If someone says “I like apple”, would it mean an apple fruit or an
Consider spam filtering in emails, we hardly notice it, but the machine does not, the machine is trained to carefully reads & track every incoming email and send it back to the respective folder. The first known mail-filtering program to use a naive Bayes classifier was Jason Rennie’s ifile program, released in 1996 . Naive Bayes algorithm uses Bayes’ theorem. The below equation calculates the chance that event A has occurred given that event B occurred.
The Problem Statement
User Experience as a discipline has attained a state of maturity over the years. As years passed the domain got matured in the areas of the design principles, design process, user’s expectation from a product, technical literacy of the users and the advancement of technology frameworks. However, data is still considered a far fetching strategy in formulating UX design decisions. Data Driven decision is considered more reliable than relying on human empathy as it gives a solid scientific ground to support a hypothesis. In a typical UCD process data is taken into consideration only if there is
The future of User experience will be driven by data. Data certainly has the ability to make human lives better by crafting meaningful interactions through predictive systems. Practically in each circle of human
life, a specific amount of data gets exuded through connections which get caught in some frame. Dietary habits, reading habits, travel habits when given a choice between mountains or a beach, browsing habits, gym habits are all data which are getting stored digitally. Habit changes over time due to the influence of various factors, like getting exposed to a different culture, due to the occurrence of a
In the dynamic world human being come across several events which shape their short term & long term thinking. A
Designers rely on personas to build a system. Users Persona is a representation of a character and acts as a reference point for designers. While designing products for a specific user group a user persona helps
Embrace Quantitative Research
Recognizing the future by sitting in the present is remarkably a challenging proposition for a machine. To do that machine needs to interpret the present and apply futuristic variables to predict a future outcome. User research forms the core of UX Design.
on data and use a statistical model to prove a hypothesis. Over time as the data keeps growing a pattern is identified which can help build a predictive model.
Identify Patterns in the Data
Imagine a user plays golf only on the weekend, or read books during the morning. A user does online shopping only when his car is out for servicing. A user logs into the internet at night to check personal emails. A user does reckless shopping every first week of the month. A user visits the local pub every Thursday. If all of the above-mentioned activities are repetitive then it becomes a pattern. Once you start mining the data you can find a pattern which further helps in understanding a user better and predict actions. Machine intelligence can analyze thousands of variables across terabytes of data, potentially uncovering subtle but significant relationships .
Measure the Change
Change is inevitable in every corner of the human ecosystem.
The world is moving towards machine intelligence and artificial decision-making systems. While research