Explore AI generated designs, images, art and prompts by top community artists and designers.
Scene: In an office at night , the protagonist is working overtime alone. The phone suddenly lights up with an encrypted file transfer request from an unknown number , and a pop-up window on the computer displays "Overseas Customer Cooperation Plan". A close-up shot shows the protagonist inserting a USB drive into the host to copy data , and a mysterious person in the dark behind is remotely controlling the camera. Scene style: Comic style Color scheme: Dark blue night sky color + dangerous red embellishment Dynamic elements: Flashing computer indicator light/USB drive data flow special effects Detail presentation: Screen pop-up window countdown/file transfer progress bar/hidden remote control software icon ,
"A highly realistic image of a frustrated office worker sitting at his desk , holding a cup of coffee in one hand as he stares at his computer screen with a stressed and exhausted expression. He has a furrowed brow , slightly messy hair , and visible tension in his posture. His workspace includes an open laptop , scattered papers , and additional coffee cups , suggesting long working hours. Above his head , floating icons of Adobe software such as Photoshop , Illustrator , InDesign , and After Effects represent the overwhelming workload and constant design revisions. The background depicts a modern office environment with other employees working at their desks. The lighting is slightly dim or cool-toned to emphasize the mood of overwork and fatigue." ,
Fairness means ensuring your analysis doesn't create or reinforce bias. This can be challenging , but if the analysis is not objective , the conclusions can be misleading and even harmful. In this reading , you’re going to explore some best practices you can use to guide your work toward a more fair analysis! Consider fairness Following are some strategies that support fair analysis: Best practice Explanation Example Consider all of the available data Part of your job as a data analyst is to determine what data is going to be useful for your analysis. Often there will be data that isn’t relevant to what you’re focusing on or doesn’t seem to align with your expectations. But you can’t just ignore it; it’s critical to consider all of the available data so that your analysis reflects the truth and not just your own expectations. A state’s Department of Transportation is interested in measuring traffic patterns on holidays. At first , they only include metrics related to traffic volumes and the fact that the days are holidays. But the data team realizes they failed to consider how weather on these holidays might also affect traffic volumes. Considering this additional data helps them gain more complete insights. Identify surrounding factors As you’ll learn throughout these courses , context is key for you and your stakeholders to understand the final conclusions of any analysis. Similar to considering all of the data , you also must understand surrounding factors that could influence the insights you’re gaining. A human resources department wants to better plan for employee vacation time in order to anticipate staffing needs. HR uses a list of national bank holidays as a key part of the data-gathering process. But they fail to consider important holidays that aren’t on the bank calendar , which introduces bias against employees who celebrate them. It also gives HR less useful results because bank holidays may not necessarily apply to their actual employee population. Include self-reported data Self-reporting is a data collection technique where participants provide information about themselves. Self-reported data can be a great way to introduce fairness in your data collection process. People bring conscious and unconscious bias to their observations about the world , including about other people. Using self-reporting methods to collect data can help avoid these observer biases. Additionally , separating self-reported data from other data you collect provides important context to your conclusions! A data analyst is working on a project for a brick-and-mortar retailer. Their goal is to learn more about their customer base. This data analyst knows they need to consider fairness when they collect data; they decide to create a survey so that customers can self-report information about themselves. By doing that , they avoid bias that might be introduced with other demographic data collection methods. For example , if they had sales associates report their observations about customers , they might introduce any unconscious bias the employees had to the data. Use oversampling effectively When collecting data about a population , it’s important to be aware of the actual makeup of that population. Sometimes , oversampling can help you represent groups in that population that otherwise wouldn’t be represented fairly. Oversampling is the process of increasing the sample size of nondominant groups in a population. This can help you better represent them and address imbalanced datasets. A fitness company is releasing new digital content for users of their equipment. They are interested in designing content that appeals to different users , knowing that different people may interact with their equipment in different ways. For example , part of their user-base is age 70 or older. In order to represent these users , they oversample them in their data. That way , decisions they make about their fitness content will be more inclusive. Think about fairness from beginning to end To ensure that your analysis and final conclusions are fair , be sure to consider fairness from the earliest stages of a project to when you act on the data insights. This means that data collection , cleaning , processing , and analysis are all performed with fairness in mind. A data team kicks off a project by including fairness measures in their data-collection process. These measures include oversampling their population and using self-reported data. However , they fail to inform stakeholders about these measures during the presentation. As a result , stakeholders leave with skewed understandings of the data. Learning from this experience , they add key information about fairness considerations to future stakeholder presentations. ,
Create an image of a young boy standing in front of a broken mirror in a dimly lit , worn-down room. The boy wears tattered clothes and has a somber expression , his surroundings reflecting poverty and struggle. However , in the shattered fragments of the mirror , a different world is visible—his reflection shows a hopeful future: a well-dressed version of himself in a bright , successful environment , perhaps wearing a graduation gown or working in a dream career. The contrast between his reality and the dreamlike reflection should be striking , emphasizing his longing and the barriers created by poverty. ,
"Imagine transforming your room's atmosphere instantly with the power of a smart LED mood light! This innovative lighting solution lets you change the ambiance of your space with just a few taps on your smartphone. Whether you're studying , unwinding , or hosting a party , the smart LED light adapts to your needs by offering customizable colors and brightness settings. Set it to a bright , energizing light when you're working , or switch to soothing hues like blue or purple to create a calm and relaxing environment. Want to take it a step further? Sync the light with your favorite music to create a dynamic light show that reacts to every beat! It’s like having your very own light DJ for the ultimate entertainment experience. The best part? You can control the light remotely from anywhere in the room using an easy-to-use app. This smart lighting solution not only adds a personal touch to your space , but it also enhances the mood , helping you create the perfect environment for any occasion. Whether you're hosting a movie night , working , or just chilling with friends , the smart LED mood light makes every moment feel just right." ,
best quality , masterpiece , ultra high res , (photorealistic:1.8) , detailed skin , dark skin , natural breasts , beauty Japanese gal , blonde hair , beautiful detailed eye , business suit and white shirt , makeup , lipstick , mascara , eyeshadow , smile , sitting chair and working at office , perfect detailed fingers ,
A photorealistic portrait of a ((determined|resilient|innovative)) ((scientist|researcher|inventor)) working on a transparent data visualization infographic , with a high-resolution OLED GUI interface display and annotations. The image is framed within a display case , showcasing the intricate technical drawing of a groundbreaking invention. ,
(((Space Station's interior))).There are starships of many sizes , shapes , colors , & ship condition.Some need repairs , need a refit , & others need a complete overhaul.The styles are , from Gerry and Silvia Anderson , & Judith Garfield & Reeves-Stevens.Ships are being fixed , Inside the docking bay.There is wall screen showing a research lab.Men , women , droids , cyborgs , aliens working. ,
A highly Pencil sketch image of multiple robotic arms and two young scientists sit on the table and programming and The robotic arms are state-of-the-art , with precise and synchronized movements , working on various parts of the car , assembling a race Formula car in a modern , high-tech workshop. The two young scientists , dressed in lab coats and safety gear , are actively involved in the process , monitoring and guiding the assembly. The scene is filled with detailed mechanical components and tools , showcasing the advanced technology used in the assembly process. The background features advanced machinery and a well-lit , pristine workshop environment , highlighting the meticulous and sophisticated nature of the task. ,
A highly realistic image of multiple robotic arms and two young scientists , whose faces are not visible , working on robots and robotic arms in a modern , high-tech workshop. The robotic arms are state-of-the-art , with precise and synchronized movements , being fine-tuned and calibrated by the scientists. The two young scientists , dressed in lab coats and safety gear , are positioned with their backs to the camera , actively involved in the process. The scene is filled with detailed mechanical components and tools , showcasing the advanced technology being developed. The background features advanced machinery and a well-lit , pristine workshop environment , highlighting the meticulous and sophisticated nature of their work. ,
A highly realistic image of multiple robotic arms and two young scientists sit on the table and programming and The robotic arms are state-of-the-art , with precise and synchronized movements , working on various parts of the car , assembling a race Formula car in a modern , high-tech workshop. The two young scientists , dressed in lab coats and safety gear , are actively involved in the process , monitoring and guiding the assembly. The scene is filled with detailed mechanical components and tools , showcasing the advanced technology used in the assembly process. The background features advanced machinery and a well-lit , pristine workshop environment , highlighting the meticulous and sophisticated nature of the task. ,