• Home
  • Mentoring Programs
  • Courses
  • UX BYTES
    • UX Design
    • UX Must-Reads
    • UX Psychology
    • UX Research
    • UX Storytelling
    • Customer Experience
    • Future UX
    • Information Design
  • About Me
  • Contact Us
RegisterLogin
Screenflows.com
  • Home
  • Mentoring Programs
  • Courses
  • UX BYTES
    • UX Design
    • UX Must-Reads
    • UX Psychology
    • UX Research
    • UX Storytelling
    • Customer Experience
    • Future UX
    • Information Design
  • About Me
  • Contact Us

Future UX

  • Home
  • Blog
  • Future UX
  • How AI’s greatest asset can be its greatest weakness?

How AI’s greatest asset can be its greatest weakness?

  • Posted by SP
  • Date April 22, 2019
  • Comments 0 comment
AI's_Greatest_asset_can_be_its_greatest_weakness

With thousands of new digital products crowding each slice of the market, it has become almost impossible to differentiate products. But we still trust some products, while never hesitate to curl up our brows when we face certain other products. For a product to survive and thrive in the market, companies should gain the trust of the customers. This is even more important for product companies in the AI domain because AI is still fairly new and unfamiliar to most people and this creates an aura of disbelief around anything that claims to be AI-powered. These are a few critical aspects of AI that can affect users trust in AI products. The greatest strength of AI is its autonomous intelligence. Its the same inherent autonomous nature of an AI system that creates the greatest mistrust and disbelief among the users. So what is the way out? How can we make the users’ trust in AI products? Here are a few considerations that will help us, UX designers, to improve users’ trust in AI products.

Familiarity

Familiarity with the system helps build trust and comfort with the AI system and the company. Once the user becomes familiar with the intelligent systems and understands the value of the technology through its daily use, the user validates that it is a safe technology. Once the user realizes that the system is a value add, she permits the system to collect additional data about her. This process takes time, patience and respect for user preferences.

Minimised Intrusion

The minimised intrusion approach to designing AI systems helps in building users trust and confidence in using the intelligent systems and in return improves the user experience of the systems. This can be done by allowing users to:

  1. Set system default settings at basic level with basic functionality
  2. Permit only the necessary amount of data to be collected, used and stored
  3. Change settings later on to allow more data to be collected and to shift to more advance settings. This is important because once familiarity with the system has improved and once the user realizes the system is a value add that justifies additional data collection by the system, the user would want to access the full features of the AI systems and devices through direct request or feedback loop.

Here two fundamental principles of UX are in action

Principle of Control

Users always need to feel that they have control over how a product behaves, what they can do or undo. By allowing users to have control over how the product behaves, users feel more comfortable using the product and their trust on the product increases over time.

Principle of Familiarity

From a product design perspective, it is best to build on what users already know and are familiar with. A radically different UI interaction paradigm can scare the users away.

AI systems are based on autonomous learning capabilities. When it comes to traditional non-AI systems, direct manipulation and control are feasibile. Because there is direct mapping between inputs (actions of the users) and the output (how product behaves). But this direct mapping may not always feasibile in AI system because of the behaviour of the system based on inherent autonomy. When users feel they have less control over the system behaviour, users will have less trust on them.

Taking into account these measures would reduce the possible doubts the users might have about the product and thereby deliver help the product to meet the customer’s needs and expectations.

Tag:AI, AI systems, AI-UX

  • Share:
author avatar
SP

Previous post

Businesses based only on transactional customer relationships are dying. Here is a new tactic to grow business today
April 22, 2019

Next post

What is the one problem for all businesses, yet so challenging that solving which can ensure superior customer experience?
April 25, 2019

You may also like

5_ways_to_make_AI_product_gain_social_trust
5 easy ways to make your AI product gain social trust
25 April, 2019
why_next_10_yearsof_UX_will_smash_last_10_years
Why Next 10 Years of UX Will Smash the Last 10
30 March, 2019
AI mistakes are too risky_ Here is how to fix them
AI mistakes are too risky: Here is how to fix them
27 March, 2019

Leave A Reply Cancel reply

You must be logged in to post a comment.

Recent Posts

  • Fitts Law is not even a Law !!
  • Feel that Web Developers can also Design UX?
  • Think “I know enough UX & Moving into UX is easy”? But is it really that easy?
  • Why Learning UX from Youtube & Blogs is a Very Bad Idea
  • Are you a UX Practioner? Then start telling stories.

Recent Comments

    Archives

    • August 2020
    • July 2020
    • June 2020
    • July 2019
    • June 2019
    • May 2019
    • April 2019
    • March 2019

    Categories

    • Customer Experience
    • Future UX
    • Information Design
    • UX Design
    • UX Must-Reads
    • UX Psychology
    • UX Research
    • UX Storytelling

    Meta

    • Register
    • Log in
    • Entries feed
    • Comments feed
    • WordPress.org

    Screenflows Logo

    (91) 9895841280

    [email protected]

    Company

    • Home
    • Blog
    • About Me
    • Contact Us

    Links

    • Mentoring Programs
    • Courses
    • Blog
    • About Me
    • Register

    Recommend

    • UX Design
    • UX Must-Reads
    • UX Psychology
    • UX Storytelling
    • UX Research

    Support

    • Privacy Policy
    • FAQ
    • Refund Policy
    • Terms of Use
    • Contact Us

    Copyright: Orange Factor Design Labs LLP | 2021-22

    Login with your site account

    Lost your password?

    Not a member yet? Register now

    Register a new account

    Are you a member? Login now