Showing posts with label UX and AI. Show all posts
Showing posts with label UX and AI. Show all posts

Friday, 21 January 2022

How Design Will Impact Companies in 2022 and Beyond

Impact of UX design 2022

The pandemic and changes to the nature of work continue to affect every industry, including the design world. The unpredictable business climate is forcing companies to look not only at how they interact with customers, but also with employees, partners, and other stakeholders. Businesses across the spectrum are turning to design to assess the new reality, pinpoint ways to work effectively, and prepare for a still-uncertain future. Based on my work with clients and partners through 2021, here are some thoughts on where the design industry stands in 2022 and what it will look like going forward:


  • Organizations that are still trying to pin down an exact ROI for design are wasting time. No one has cracked the code for a simple equation to show what the return is on investing in design, whether that’s design strategy, experience design, or aesthetics. At this point, it’s clear that thoughtful design is a key element to being competitive in today’s world. Most businesses have embraced design as an essential business tool, and they have either integrated a design team into their business processes, or established relationships with design consultants. Any person in company leadership that is still asking for easily quantifiable proof of the value of design is wasting time and losing ground to competitors.


  • Developing AI tools requires a human-centered approach that isn’t there right now. Looking at trends for almost any industry you are likely to see predictions that AI will be further integrated in to that industry. However, design and implementation of AI applications are lacking a human-centered approach, and that is hampering success. AI applications designed without considering the people they will impact will be less effective and alienate customers who don’t feel like their needs are a priority.


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  • Service design will have an impact in industries where it hasn’t been used before. During the pandemic, retail stores and restaurants had to change on a time to try to serve customers in a new way. Restaurants had to rethink their processes from serving customers in the dining room to taking orders online/by phone, cooking and packaging meals, collecting payment and delivering the food with minimal contact. As these industries move forward, service design can help them figure out what the future of serving their customers looks like. What systems and processes from the pandemic should stay, what pre-pandemic processes will return, and what kind of new hybrid systems should be put in place? Service design can help industries that traditionally haven’t used it to plan for a future where they can efficiently serve customers.


  • Companies need to radically re-think how they engage the human beings who deliver goods/services to their customers. The job market is mobile and volatile, and companies are scrambling to find good people and to keep them. How do you solve for both the changing nature of employment and employee experience? Beyond making things better through increased pay and benefits, companies must rethink the role of employees and support them in new and different ways. Employees aren’t just extensions of a company’s brand anymore. They are players in the business ecosystem. 


  • Digital therapeutics will continue to be a hot trend, and could spur interesting partnerships. Right now, it is mostly pharma companies that are investing in digital therapeutics and navigating the complicated process required to create, test and get approval for this kind of solution. Successful digital therapeutics must be designed by people who both know how to create clinical-level solutions and also know how to design good digital experiences for humans. This could lead to interesting partnerships within the healthcare, design, and tech industries to deliver solutions that can pass regulatory muster and will also be embraced by patients because they are effective and easy to use.


  • Companies are integrating behavior science in their business, but not all of them are doing it right. Companies are recognizing the value of behavior science in designing and developing products and solutions, and many companies are bringing in people with expertise in behavior change. Some companies will hire a couple of behavioral scientists or create a behavior change group that works in its own silo. That’s not likely to be effective. The companies that integrate behavioral science across all parts of the Organization are the ones that will reap the greatest benefits. Behavior change thinking needs to be integrated across teams and processes to truly have an impact.
  •  

    Design is having an effect on nearly every industry, in one way or another, and the role of design in business will continue to expand in 2022. Service design, user experience, behavior change, employee experience, and many other kinds of design will play a role in success and continue to influence how companies connect with stakeholders moving forward. 



About author


Jennifer Briselli - Chief Design Strategy Officer

Jennifer Briselli
Chief Design Strategy Officer, Mad*Pow

Jen's a lifelong learner with an insatiable curiosity and deep passion for science, education, and empowering people through design. Her design philosophy is less about solving people's problems for them, and more about building the tools, environments, and circumstances that enable people to improve their own lives. At Mad*Pow, she does just that, leading the delivery practices as the Chief Design Strategy Officer.
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Sunday, 23 August 2020

Compatibility of Internet of Things (IoT) and User Experience (UX)

Internet of Things (IoT) and User Experience (UX)


Internet of Things (IoT)
The Internet of Things (IoT) is one of the fastest-growing fields which is driving new ways for interacting with appliances, tools, and devices in entirely new and unexpected ways. IoT is becoming a bigger part of our everyday lives — from our gym and walks to travel planning, home security, and countless other uses. As IoT devices become more common the user experience of using such devices becomes increasingly important. Being a new technology and on the other hand addressing the fact that users have a very low tolerance for the inconvenience of learning something new or doing something differently. That’s why user experience is very vital for IoT products.

Initially, IoT solutions focused primarily on technical capabilities. But with more than one-third of these new objects and services are abandoned by their users after only 6 months of use, it became a primary result of the fact that IoT significantly depends on the UX design for the connected objects. The UX community being new to IoT projects, there is still a lot to be done to develop new best practices specifically for IoT projects.




UX for IoT is different and complex because there are two sequences of interaction ie from user to the virtual system and from the virtual system to the physical system. Also, each physical system has its own set of interactions and moreover there are different users to use the application. Hence the designers have to face new challenges while working on IoT projects.

Therefore, as UX experts we need to know some of the challenges of IoT and find out if we can address them to provide good user experience for our users.

1. Connectivity issues
Internet of Things as its name suggests is primarily based on network connection as the internet is needed to transfer data between the app and physical devices. Most of the IoT devices require a good WiFi network.
We are used to occasional connectivity problems on our smartphones and computers like poor connection during a video call, slow websites, etc. Whereas we don't expect such problems with our physical devices like toasters, room lighting, and opening or closing doors. The user experience expectation of everyday physical things is different from that of the web. When we turn on room light, we expect an immediate response or else we assume that there is some defect with light. But when the internet connection is poor it may take a couple of minutes for the lights to turn on. The users might not be ready for such delays in response from physical products and might lead to frustration, worry or abandoning of IoT system. The first generation users certainly have to go through such problems.
Connectivity issues are going to have a significant impact on the IoT experience and there is little we can do about it since it is a technical problem.


2. Multiple apps for different devices
One of the main problems with IoT devices functioning is that there are plenty of connected devices. Individually these devices might be smart and useful, but as a team, they might not work in sync. Users need different apps for different devices and this becomes overwhelming and a plenty of mental overloads. In the current scenario, users cannot control the whole collection of IoT devices from a single app and make them sync the data. So for instance, if you have a smart car, a smart gym, and a smart toaster, and you have different apps to control them. You won’t be able to apply the rule to adjust the temperature in the room according to your workout data and start your toaster after 30 mins of workout and start your smart car as soon as you lock the door from outside. This does not give a unanimous user experience of all IoT products. This kind of broken UX can make the tasks more complicated whereas the purpose of smart devices is to make the user’s life easier. Another example can be lots of smart home apps don’t work together for example, a user might control the sound system with one app and lights with another. Even in some cases, lighting from different manufacturers may require different apps to control, which leads to bad user experience.

3. Synchronising Data
Another IoT design challenge is to separate the useful and irrelevant data while a lot of data is flowing from various sources and devices. Synchronising data flow between different smart devices is the key to UX design in the IoT platform and is also a difficult task.


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4. Third-party integrations
UX designers rely on the supplies from many third-party vendors to develop an IoT device. Different components (sensors, processors, controllers) from different vendors can be difficult to integrate and lead to disoriented user experience. Supplies such as application processors, sensors, controllers, and platforms may not all come from one supplier. Expecting different pieces to work together to produce a seamless UX might be impossible. IoT devices require repairs and updates after a certain interval. Third-party integrations are not always seamless.

5. Impact of hardware
Hardware is a big part of the solution in IoT products and, depending on its type and quality it has a large effect on the user experience. Hardware selection is generally based on the technical specifications, compatibility of running software and cost to the user. The combination of hardware impacts user experience to a large extent. In case the user chooses a lower-cost system, some functionality might not be applicable which compromises the user’s experience. Therefore it is important to select appropriate hardware components.

Conclusion
The key to creating great IoT user experiences lies in understanding the fluid nature of IoT and designing interaction for it. A good user-research is a must to understand the user’s expectations from IoT devices. The fundamentals always remain the same, just that the designer needs to spend more time understanding how IoT works.
In the IoT domain, a user task flow may span different devices, different interaction paradigms, and different contexts of use. This increases complexity by orders of magnitude for the designer. Conversely, user expectations are also increased because users expect the experience of using these disparate connected devices in concert to be more than the sum of their individual experiences.

About Author
Author profile picture Neha Srivastava

Neha Srivastava
Manager | User Experience | HCL Technologies, Noida 
Email   |  LinkedIn 


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Tuesday, 11 February 2020

Astounding Artificial Intelligence Statistics for 2020

Artificial intelligence statistics 2020



Artificial intelligence is poised to transform the way we live, from everyday tasks to complex, large-scale projects. Our future will be molded by machine learning and automated systems. These mind-warping artificial intelligence statistics are all you need to prepare you for the artificial intelligence revolution.

Key artificial intelligence facts, editor’s pick

  • Chatbots are expected to cut business costs by $8 billion.
  • About 15% of surveyed companies use AI, primarily for improving customer experience.
  • The percentage of help-wanted ads requiring AI skills is 4.5 times higher than in 2013.
  • The median salary for senior computer scientists and managers in  machine learning is more than $127,000.
  • Google’s deep learning prediction algorithm correctly diagnoses suspected tumors 89% of the time by analyzing medical heatmaps.

Artificial intelligence has come a long way since IBM introduced a mainframe that could play a competitive game of checkers. Today’s advanced AI systems are transforming the economy, culture, and even politics.

Current AI technology can be roughly divided into “weak” and “strong” AI. A perfect example of weak AI can be found in your living room in the form of smart speakers. Siri, Echo, and Alexa all have programmed responses to certain demands.




Strong AI, on the other hand, is the most important and interesting artificial intelligence technology today. Strong AI is the kind of AI featured in sci-fi movies. It aims to emulate the human cognitive process by grouping various concepts together in associational clusters. While strong AI has a long way to go before we see widespread use, there’s no doubt that it will profoundly change our lives once it passes the prototype stage.

All in all, scientists believe that the future scope of artificial intelligence will encompass almost all human activities. Here are some AI statistics to prepare you for the brave new world that lies ahead of us.

Chatbot Statistics

1. According to Gartner’s AI customer service statistics, chatbots will be responsible for 85% of customer service by 2020

(Gartner)
Artificial intelligence is still far away from taking over sales jobs, but it has proved more than useful in the customer service department. Modern chatbots learn by trial and error and gradually improve their understanding of customers’ questions. Customer service is the first among many boring jobs that will be taken over by AI.

2. According to Crunchbase’s AI stats, more than 10,000 developers now work on building chatbots for Facebook Messenger.

(Crunchbase)
Facebook has proved itself an excellent platform for businesses to share their products. In fact, many companies use Messenger as a dedicated customer service platform.

3. Juniper’s statistics about artificial intelligence say that chatbots could save businesses $8 billion.

(Juniper)
Although many companies already outsource customer service and try to save money that way, the truth is, it’s still expensive. Thankfully, we’re not that far from a future where AI will handle almost all customer service.


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Business and AI Statistics

4. An Adobe artificial intelligence report says that only 15% of surveyed companies use AI – primarily for improving customer experience.

(Adobe)
However, the artificial intelligence statistics also reveal that 31% of those not currently using AI intend to use it within the next 12 months. In addition to improving CX through on-site personalization, companies also rely on AI and data to refine their marketing methods.

5. Start-up companies that use artificial intelligence have increased 14-fold in number since 2000.

(Stanford)
The popularity of artificial intelligence has quite literally surged in the past two decades. With such impressive momentum, there’s no doubt we will see a huge supply of jobs in artifical intelligence.  AI courses have increased ninefold in academia in the last 20 years. Enrollment in AI-related courses at Stanford has surged 4,500%.

6. The percentage of help-wanted ads requiring AI skills is 4.5 times higher than in 2013.

(Stanford University)
While it was believed that AI technology would be replacing humans in the workplace by now, causing widespread unemployment, the truth is quite the opposite. With more and more companies using AI, there will be a steady increase in demand for experts in the field.


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7. The three most desired AI skills on Monster.com are machine learning, deep learning, and natural language processing

(Forbes)
It’s also worth noting that the average machine learning manager makes a salary of $127,000 or more. Artificial intelligence experts earn an enviable salary.

8. 84% of company representatives believe that investing in AI can bring more competitive advantages.

(Statista)
In fact, according to Statista AI industry statistics, 75% believe that AI has the potential to open up new businesses. They think AI and business will be inseparable, especially when it comes to giving entrepreneurs a better foothold in existing markets. About 63% state that the shift to AI will be primarily driven by a desire to cut operating costs.

9. Forbes AI statistics state that 87% of early AI adopters say they are using or considering using AI for sales forecasting and improving email marketing.

(Forbes)
In addition, 61% use artificial intelligence for market forecast purposes. AI can efficiently navigate the hectic world of international commerce by applying big data analysis and pattern recognition in real-time, enabling marketers to create valid long-term strategies.

10. 40% of business leaders believe AI will increase worker productivity.

(Accenture)
Accenture’s AI work statistics say AI has the potential to double annual economic growth rates by 2035. In addition to financial gains, AI’s biggest potential lies in the fact that it can fundamentally change the nature of work and the relationship between humans and technology.




Credits: This article is originally published at Kommando Tech


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Jovan Milenkovic
Kommando Tech

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