The Fundamental Differences between GraphQL and REST APIs

December, 13 2019 |

      If you’re thinking about how you should design your next web API, look no further! We will cover the fundamental differences between GraphQL and REST in the following article. Before diving into each architectural style I would like to give a quick synopsis of both methodologies. REST stands for Representational state transfer which basically breaks down to a style of web architecture that has many underlying characteristics and manages the behavior of clients and servers. A REST API defines a set of functions in which software developers can perform requests and receive responses via HTTP protocol such as a (GET/POST/UPDATE/DELETE). Lastly, an API can be considered RESTful if it has the following characteristics: Client-server, Stateless, and Cacheable. 

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The UX of Autonomous Vehicles

       The autonomous vehicle is more than just a blurred dream that is still off in the distant future; it’s already happening. Recently, the first self-driving taxi service has been launched in Singapore. It is predicted that it’s only a matter of a couple of years before fully automated driving vehicles will be available for purchase on the consumer’s market (Tesla is already taking incremental steps to make semi-autonomous driving vehicles available to the public). However, only a few companies like Google and Volvo have been testing fully automated driving cars on public roads. 

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Great Expectations (Writing a Great SOW)

      The best way to ensure a successful partnership with a consultancy is to have a solid shared understanding of what the goals of the project are, what work will be done, how it will be done, and when it will be done. The Statement of Work (SOW) governing project work is the foundation for a successful outcome. This article explores how to take a high-level SOW from an accepted proposal and turn it into a robust and effective contract.

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Should Designers and Researchers Sign Their Own Hippocratic Oath?

     In this era, designers and researchers with all types of backgrounds are becoming strategic leaders and specialists in creating new products, businesses, and services. While these leaders from all walks are coming into positions of power in which we have breathtaking technological capabilities, should we not feel an obligation to do no harm? Healers agree to a Hippocratic oath- upholding them to maintain ethical standards in the work they do. Detrimental and questionable products and features have been created when power and feasibility can turn honest intentions into design decisions that alienate and do harm to the very people that the product was created to protect.

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Facial Recognition Technology and Racial Biases

         In 2018, research reports from the ACLU emerged indicating that Amazon’s facial recognition technology had reportedly “confused” the faces of 28 congressmen with the faces of known criminals. Let’s unpack that statement. First, Amazon has been developing facial recognition technology, called Rekognition, which can provide “highly accurate facial analysis and facial recognition on images and video.” In 2018, Amazon was actively making movements towards selling this technological tool to law enforcement. The ACLU, among other organizations and individuals, were concerned with the implications of utilizing such technology.  In turn, the ACLU conducted its own study employing Rekognition facial technology. Their research uncovered that Rekognition technology was not as accurate of a facial recognition tool as had been perceived, and resulted in a large number of mismatched faces. Most importantly, the ACLU reported that Rekognition disproportionately misidentified faces of people of color- as highlighted by the 28 faces of congressmen that were misidentified as being the faces of known criminals. While Amazon and the ACLU debated over these results, the findings published by the ACLU point towards a bigger issue- in what ways are racial biases manifesting themselves in facial recognition technology and how can this cause harm to communities of color?

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Creating a Custom Material UI Theme Part 3: Customizing Individual Components

November, 15 2019 | How-To, Emerging Trends, User Interface

      Many of the components for Material UI are easy to customize. For components such as Badges and Circular Progress, you can add color options by adding an additional variant to the theme. For instance, when calling a badge using a primary color, you would use <Badge color=”primary” />. In order to use an info color, you could use <Badge color=”info” />, and add under MuiBadge : { colorInfo: {…}} to the theme. You can interchange “info” with any color name you choose.

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Happy World Usability Day!


   The theme of this years’ World Usability Day: “Design for the Future We Want”. The theme is inspired by the United Nations’ Sustainable Development GoalsDesign can help solve some of the world’s most challenging problems. Design has the opportunity to create a better world for all by creating products that cause no harm, make the world a better place to live and support our humanity: For example, design could persuade people to consume more sustainably or it could potentially help prevent the spread of fake news.

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Machine Learning for Recommendations on Streaming Services

        Oftentimes, when trying to decide what shows or movies to watch on our favorite streaming services, we look at what is being recommended to us. Most TV shows and movies we watch on streaming services (like Netflix, Hulu and Amazon Prime) are discovered through an algorithm that informs the recommendation system. The following article focuses specifically on the recommendation systems in Hulu mobile App and Netflix TV, and the way in which machine learning can be applied to improve this algorithm. [Read More]

Data Visualization and Qualitative Reports

October, 04 2019 |

         When writing reports, we are often looking for the best ways to effectively synthesize and communicate our findings to a larger audience. Implementing data visualizations into qualitative report writing is an effective tool that can enhance how findings are presented and understood by those who will be reading the report, as it works to help create a shared understanding of what the main findings are.  Effectively utilizing data visualizations in report writing can help to express concepts or findings in a quick, easy, and memorable manner. 

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Don't Turn a Blind Eye to Website Accessibility

September, 25 2019 |

        On May 28, 1988, a young woman with cerebral palsy, Lisa Carl, went to her neighborhood movie theater to see a film but was denied entry because of her wheelchair. The theater manager refused to accommodate Lisa and wouldn’t take her money. When questioned later, the manager said, “I don’t have to let her in.” Lisa told this story during testimony to Congress, saying “I was not crying on the outside but I was crying on the inside. I just wanted to watch the movie like everyone else.”

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