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Messages - Abdus Sattar

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Science and Information / Can an AI keep you happy at work?
« on: February 17, 2020, 02:52:31 PM »
Can an AI keep you happy at work? Ex-Google team reveal software that 'nudges' workers with messages throughout the day

- The startup, called Humu, uses AI to 'nudge' staffers to complete certain tasks
- Uses machine learning to analyze data and find areas they can improve upon
'- Nudges' are then delivered to managers and staff via emails or text messages

Three former Google employees believe that artificial intelligence could be the secret to making you happier at work.

Their startup, called Humu, uses machine learning to parse through employee data and then 'nudges' workers to help them improve in areas that might make their work lives better, according to the New York Times.

Nudges are delivered to employees via emails or text messages and are expected to motivate employees around small tasks, with the eventual goal of improving the broader organization as a whole

Humu was founded in 2017 and now counts 15 companies, both big and small, as its customers, according to the Times.

It's based around a 'nudge engine' that encourages people to make decisions based on what's in their best interest, instead of making decisions based on what is easiest.

These same principles were used by the human resources team at Google, which sought to motivate employees to save money, waste less food and make other proactive choices.

'Often we want to be better people,' Laszlo Bock, Humu’s chief executive and Google’s former leader of people operations, told the Times.

'We want to be the person we hope we can be. But we need to be reminded.

'A nudge can have a powerful impact if correctly deployed on how people behave and on human performance.'

Humu uses machine learning to streamline content sent to customers, as well as timing and how messages are delivered based on how employees respond, the Times noted.

Each nudge is tailored for a different purpose and many of Humu's customers have them sent only to managers.

For example, a manager might be 'nudged' to remember to ask members of their team for their input, while an employee might be nudged to come up with questions for their manager. 

One of Humu's customers, the salad chain Sweetgreen, used Humu to determine that a fewer-than-expected number of employees believed they had opportunities to advance their careers at the company.

Humu recommended that store managers have individual meetings with staff members to discuss advancement opportunities.

A nudge sent to one Sweetgreen manager read: 'Consider what skills each team member needs to be successful, both in their current role and longer term in their career.

AI systems rely on artificial neural networks (ANNs), which try to simulate the way the brain works in order to learn.

ANNs can be trained to recognise patterns in information - including speech, text data, or visual images - and are the basis for a large number of the developments in AI over recent years.

Conventional AI uses input to 'teach' an algorithm about a particular subject by feeding it massive amounts of information.   

AI systems rely on artificial neural networks (ANNs), which try to simulate the way the brain works in order to learn. ANNs can be trained to recognise patterns in information - including speech, text data, or visual images

Practical applications include Google's language translation services, Facebook's facial recognition software and Snapchat's image altering live filters.

The process of inputting this data can be extremely time consuming, and is limited to one type of knowledge.

A new breed of ANNs called Adversarial Neural Networks pits the wits of two AI bots against each other, which allows them to learn from each other.

This approach is designed to speed up the process of learning, as well as refining the output created by AI systems.

Take notes. Preparing this list of skills will help you spot opportunities for your team as they arise — so it’s worth putting the work in now!'

As a result, the Sweetgreen manager learned that employees wanted to diversify their skills.

That said, experts have noted there could be risks to the application, as it could push workers to complete tasks that are more beneficial to the employer, instead of their own personal interests, the Times reported.

'The companies are the only ones who know what the purpose of the nudge is,' Todd Haugh, an assistant professor of business law and ethics at Indiana University, told the Times.

'The individual who is designing the nudge is the one whose interests are going to be put in the forefront.'


বেশী বেশী পেয়ারা খাইতে হবে তাহলে।

Hope it will work soon.

true indeed

সেইদিন পরলাম এইটা কিন্তু নতুন সমাধানটা বুঝা কিন্তু সহজ না। 

Faculty Sections / Re: Magic of the Maldives ...
« on: December 11, 2019, 08:03:37 PM »
পিকগুলা দেখিয়া যাইবার জন্যে উদগ্রীব হইয়া গেলাম।

Pharmacy / Re: আদা খান, সুস্থ থাকুন
« on: June 23, 2019, 12:09:42 PM »
Thanks for sharing

উপকারী পোষ্ট।

বাইরে পড়তে যেতে ইচ্ছুক ছাত্র-ছাত্রীদের জন্যে খুবই দরকারী পোষ্ট।

Latest Technology / User Experience in Artificial Intelligence
« on: May 28, 2019, 01:03:32 PM »
User Experience in Artificial Intelligence

Two years back, Toyota offered us a glimpse into their version of the future where surprisingly, driving is still fun. Concept-i is the star in the autonomous future where people are still driving. And in the case of Toyota, it's so much fun because they're cruising along with their buddy Yui, an AI personality that helps them navigate, communicate and even contributes in their discussions.

Yui is all over the car, controlling every function and even taking the wheel when required to. It's definitely an exciting future where the machine sounds and “feels” like a human, even exhibiting empathetic behaviour.

Related: Preparing for the Future of AI

That's the kind of future I'd imagine awaits user experience (UX) in the world of AI. A time when the human-AI connection is so deep that some experts say there will be “no interface.” But currently, UX does depend on an interface. It requires screens, for instance, and they don't do much justice to it. Integrating AI into the process will mean better experience all around.

From websites to homes and cars, here's how AI could help patch the holes and bring UX closer to maximum potential.

1. Complex data analysis.
Until now, to improve user engagement in their products, UX teams have turned to tools and metrics such as usability tests, A/B tests, heat maps and usage data. However, these methods are soon to be eclipsed by AI. It's not so much because AI can collect more data -- it's how much you can do with it.

Using AI, an ecommerce store can track user behaviour across various platforms to provide the owner with tips on how they can improve their purchasing experience, eventually leading to more sales. AI can be used to tailor the design to each user’s specifications, based on the analysis of the collected data.

All this is achieved through the application of deep learning that combines large data sets to make inferences. Additionally, these systems can learn from the data and adjust their behaviour accordingly, in real time. Thus, designers applying AI in their work are likely to create better UIs at a faster rate.

2. Deeper human connection.

By analysing the vast amount of data collected, AI systems can create a deeper connection with humans, enhancing their relationship. This is already happening in a couple of industries. When you think of Siri, you see a friendly-voiced (digital) personal assistant. When Amazon first introduced Alexa, it took the market by storm. But its usefulness could only be proven over time. And it was. Smart-home owners are using it to do a million things, including scouring the internet for recipes, schedule meetings and shop. It's also being used in ambulances. Even Netflix’s highly predictive algorithm is a case example of AI in use.

Toyota says Concept-i isn't just a car, but a partner. From the simulation video, you can see that Yui connects with the family on a level that current UX doesn't reach.

By using the function over and over, consumers end up establishing an interdependent relationship with the system. That's exactly how AI is designed to work. You use the system; it collects data; it uses it to learn; it becomes more useful; gives better user experience; you use it more as it collects data, learns and becomes more useful; and the cycle continues. You don't even see it coming -- and before you know it, you're deeply connected.

3. More control by the user.

A common concern about the adoption of AI to everyday life is whether the machines might eventually rise and take over the world. In other words, users are concerned about losing control over the systems. It's a legitimate concern with the autonomous cars, robots guards and smart homes expected to become commonplace.

This lack of control is mirrored in the skepticism for the future, but it can also be seen in commerce and other areas where user experience is of great importance. For instance, a user will be more likely to enter their card information into a system if they feel they have control over when money is transferred, to whom it goes and that they can retrieve it in case something goes wrong.
As AI develops, users will gain more control over the system, gradually improving trust which will lead to more usage.

In Which AI Could Enhance Your Company's UX

UX design is about a designer trying to communicate a machine's model to the user. Meaning, the designer is trying to show the user how the machine works and the kind of benefits they can get from it, from the former's point of view.

Traditionally, this involved following certain rules, and designers understood them very well. A designer knows how to create a web page by following certain rules that they can probably manipulate. With AI, however, the design is dependent on a complex analysis of data instead of following sets of rules. To be able to design using AI, designers will have to really understand the technology behind it.

Mixing UX and AI as we can have played with “AIBO”

Artificial intelligence
Artificial intelligence (AI), the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings. The term is frequently applied to the project of developing systems endowed with the intellectual processes characteristic of humans, such as the ability to reason, discover meaning, generalize, or learn from past experience. Since the development of the digital computer in the 1940s, it has been demonstrated that computers can be programmed to carry out very complex tasks - as, for example, discovering proofs for mathematical theorems or playing chess - with great proficiency. Still, despite continuing advances in computer processing speed and memory capacity, there are as yet no programs that can match human flexibility over wider domains or in tasks requiring much everyday knowledge. On the other hand, some programs have attained the performance levels of human experts and professionals in performing certain specific tasks, so that artificial intelligence in this limited sense is found in applications as diverse as medical diagnosis, computer search engines, and voice or handwriting recognition.

What Is Intelligence?
All but the simplest human behaviour is ascribed to intelligence, while even the most complicated insect behaviour is never taken as an indication of intelligence. What is the difference? Consider the behaviour of the digger wasp, Sphex ichneumoneus. When the female wasp returns to her burrow with food, she first deposits it on the threshold, checks for intruders inside her burrow, and only then, if the coast is clear, carries her food inside. The real nature of the wasp’s instinctual behaviour is revealed if the food is moved a few inches away from the entrance to her burrow while she is inside: on emerging, she will repeat the whole procedure as often as the food is displaced.

Fixing the AI in real time
Problem solving, particularly in artificial intelligence, may be characterized as a systematic search through a range of possible actions in order to reach some predefined goal or solution. Problem-solving methods divide into special purpose and general purpose. A special-purpose method is tailor-made for a particular problem and often exploits very specific features of the situation in which the problem is embedded. In contrast, a general-purpose method is applicable to a wide variety of problems. One general-purpose technique used in AI is means-end analysis—a step-by-step, or incremental, reduction of the difference between the current state and the final goal. The program selects actions from a list of means—in the case of a simple robot, this might consist of PICKUP, PUTDOWN, MOVEFORWARD, MOVEBACK, MOVELEFT, and MOVERIGHT—until the goal is reached.

Many diverse problems have been solved by artificial intelligence programs. Some examples are finding the winning move (or sequence of moves) in a board game, devising mathematical proofs, and manipulating “virtual objects” in a computer-generated world.
About Author
Jagannathan Kannan
UX Lead Designer @ Verizon wireless


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