Showing posts with label interfaces. Show all posts
Showing posts with label interfaces. Show all posts

29 October 2025

🤖〽️Prompt Engineering: Copilot Unabridged (Part 110: The Mere-Exposure Effect - How Familiarity Breeds Trust)

Prompt Engineering Series
Prompt Engineering Series

Prompt: "write a post of 600 words on mere-exposure effect in AI"

Introduction

The mere-exposure effect, first identified by psychologist Robert Zajonc in 1968, describes how people tend to develop a preference for things simply because they are familiar with them. Whether it's a song, a face, or a brand logo, repeated exposure often leads to increased liking. In recent years, this effect has found a new frontier: artificial intelligence. As AI systems become more integrated into our daily routines - from voice assistants to recommendation engines - the mere-exposure effect is quietly influencing how we perceive and accept these technologies.

The Psychology Behind Familiarity

At its core, the mere-exposure effect is about cognitive fluency. When we encounter something repeatedly, our brains process it more easily, which feels good and leads to positive associations. This mechanism is especially powerful in shaping attitudes toward novel or initially ambiguous stimuli - like AI. Early interactions with AI might feel strange or even unsettling, but over time, familiarity breeds comfort. This is particularly relevant given the 'black box' nature of many AI systems, where users don’t fully understand how decisions are made [2].

AI in Everyday Life: From Novelty to Normalcy

AI has transitioned from a futuristic concept to a routine part of modern life. Consider how often people interact with AI without even realizing it: autocomplete in search engines, personalized playlists, smart home devices, and customer service chatbots. Each interaction reinforces familiarity. A 2024 study on AI psychology suggests that as exposure increases, users report higher trust and lower anxiety about AI systems [1]. This shift is part of what researchers call the 'next to normal' thesis - AI is no longer a novelty but a normalized tool.

Mere-Exposure in Digital Interfaces

Recent research comparing the mere-exposure effect across screens and immersive virtual reality (IVR) found that increased exposure consistently enhanced user preference in both environments. This has implications for AI interfaces: the more users engage with AI through familiar platforms - like smartphones or VR headsets - the more likely they are to develop positive attitudes toward the technology. It also suggests that design consistency and repeated interaction can be strategic tools for improving user experience and trust.

Implications for AI Safety and Ethics

While the mere-exposure effect can foster acceptance, it also raises ethical questions. Familiarity might lead users to overlook risks or blindly trust AI systems. For example, people may accept biased recommendations or privacy-invasive features simply because they’ve grown accustomed to them. This underscores the importance of transparency, education, and regulation in AI development. Designers and policymakers must ensure that increased exposure doesn’t lead to complacency or misuse.

Balancing Familiarity with Understanding

The mere-exposure effect is a double-edged sword. On one hand, it helps integrate AI into society by reducing fear and resistance. On the other, it can mask complexity and encourage passive acceptance. To harness its benefits responsibly, AI developers should pair exposure with explainability. When users understand how AI works, they’re more likely to engage critically rather than just comfortably.

Conclusion

The mere-exposure effect is a subtle yet powerful force shaping our relationship with AI. As AI becomes more embedded in our lives, repeated interactions are making it feel more trustworthy, approachable, and indispensable. But with this growing comfort comes a responsibility: to ensure that familiarity doesn’t replace informed engagement. By recognizing the psychological dynamics at play, we can build AI systems that are not only accepted - but also understood and ethically sound. 

Just try the prompt on Copilot or your favorite AI-powered assistant! Have you got a different/similar result? How big or important is the difference? Any other thoughts?
Just share the link to the post with me and I'll add it to this post as a resource!

Disclaimer: The whole text was generated by Copilot (under Windows 11) at the first attempt. This is just an experiment to evaluate feature's ability to answer standard general questions, independently on whether they are correctly or incorrectly posed. Moreover, the answers may reflect hallucinations and other types of inconsistent or incorrect reasoning.

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References: 

[1] Daniel Hepperle & Matthias Wölfel (2024) Exploring Ecological Validity: A Comparative Study of the Mere Exposure Effect on Screens and in Immersive Virtual Reality, Advances in Visual Computi (ISVC 2024)

[2] Yoshija Walter (2024) The Future of Artificial Intelligence Will Be “Next to Normal”—A Perspective on Future Directions and the Psychology of AI Safety Concerns, Nat. Anthropol 2(1),

08 October 2025

🤖〽️Prompt Engineering: Copilot Unabridged (Part 106: The Future of AI - From Tools to Intelligent Companions

Prompt Engineering Series
Prompt Engineering Series

Prompt: "write a post of 600 words that depicts the evolution of AI over next years related to its integration around topics like Agentic AI, multimodal fusion, and ambient intelligence"

Introduction

Artificial Intelligence (AI) is rapidly evolving from a set of specialized tools into a pervasive, intelligent presence woven into the fabric of our daily lives. Over the next few years, three transformative trends - Agentic AI, Multimodal Fusion, and Ambient Intelligence - will redefine how we interact with machines, how machines understand us, and how they seamlessly integrate into our environments.

Agentic AI: From Assistants to Autonomous Agents

Agentic AI represents a shift from passive assistants to proactive, goal-driven entities capable of reasoning, planning, and acting independently. Unlike traditional AI systems that wait for user input, agentic AI can initiate tasks, make decisions, and adapt strategies based on changing contexts.

Imagine an AI that not only schedules your meetings but negotiates time slots with other participants, books venues, and even prepares relevant documents - all without being explicitly told. These agents will be capable of long-term memory, self-reflection, and learning from experience, making them more reliable and personalized over time.

In the coming years, we’ll see agentic AI embedded in enterprise workflows, healthcare diagnostics, and even personal productivity tools. These agents will collaborate with humans, not just as tools, but as partners - understanding goals, anticipating needs, and taking initiative.

Multimodal Fusion: Understanding the World Like Humans Do

Human cognition is inherently multimodal - we process language, visuals, sounds, and even touch simultaneously. AI is now catching up. Multimodal fusion refers to the integration of diverse data types (text, image, audio, video, sensor data) into unified models that can understand and generate across modalities.

Recent advances in large multimodal models (LMMs) have enabled AI to describe images, interpret videos, and even generate content that blends text and visuals. In the near future, this capability will become more refined and accessible. For instance, a multimodal AI could watch a security camera feed, detect anomalies, describe them in natural language, and alert relevant personnel - all in real time.

This fusion will also revolutionize creative industries. Designers, filmmakers, and educators will collaborate with AI that can understand their sketches, voice commands, and written instructions to co-create immersive experiences. The boundaries between media types will blur, giving rise to new forms of expression and interaction.

Ambient Intelligence: The Invisible Interface

Ambient intelligence is the vision of AI that’s always present, context-aware, and unobtrusively helpful. It’s the culmination of sensor networks, edge computing, and intelligent systems working in harmony to create environments that respond to human needs without explicit commands.

In smart homes, ambient AI will adjust lighting, temperature, and music based on mood and activity. In healthcare, it will monitor patients passively, detecting early signs of illness through subtle behavioral changes. In workplaces, it will optimize collaboration spaces, manage energy usage, and ensure safety - all without interrupting the flow of work.

The key to ambient intelligence is trust and transparency. As these systems become more autonomous, ensuring ethical behavior, privacy, and user control will be paramount. Advances in explainable AI and federated learning will help build systems that are both powerful and respectful of user agency.

The Road Ahead

The convergence of agentic AI, multimodal fusion, and ambient intelligence signals a future where AI is no longer confined to screens and commands. Instead, it becomes a seamless extension of our cognition and environment - an intelligent layer that enhances human capabilities.

However, this evolution also demands thoughtful governance. As AI becomes more autonomous and pervasive, we must address questions of accountability, bias, and societal impact. The challenge is not just technical but ethical: how do we ensure these systems serve humanity equitably and responsibly?

In the coming years, the most successful AI systems won’t just be the smartest - they’ll be the most empathetic, transparent, and aligned with human values. The future of AI is not just about machines that think, but about machines that understand, adapt, and collaborate.

Just try the prompt on Copilot or your favorite AI-powered assistant! Have you got a different/similar result? How big or important is the difference? Any other thoughts?
Just share the link to the post with me and I'll add it to this post as a resource!

Disclaimer: The whole text was generated by Copilot (under Windows 11) at the first attempt. This is just an experiment to evaluate feature's ability to answer standard general questions, independently on whether they are correctly or incorrectly posed. Moreover, the answers may reflect hallucinations and other types of inconsistent or incorrect reasoning.

Previous Post <<||>> Next Post

28 November 2007

🏗️Software Engineering: Interfaces (Just the Quotes)

"A good information system both exposes interface errors and stimulates their correction" (Fred P Brooks, "The Mythical Man-Month: Essays", 1975)

"By the architecture of a system, I mean the complete and detailed specification of the user interface. For a computer this is the programming manual. For a compiler it is the language manual. For a control program it is the manuals for the language or languages used to invoke its functions. For the entire system it is the union of the manuals the user must consult to do his entire job." (Fred P Brooks, "The Mythical Man-Month: Essays", 1975)

"Clearly, methods of designing programs so as to eliminate or at least illuminate side effects can have an immense payoff in maintenance costs. So can methods of implementing designs with fewer people, fewer interfaces, and hence fewer bugs." (Fred P Brooks, "The Mythical Man-Month: Essays", 1975)

"With increasing size and complexity of the implementations of information systems, it is necessary to use some logical construct (or architecture) for defining and controlling the interfaces and the integration of all of the components of the system." (John Zachman, "A Framework for Information Systems Architecture", 1987)

"Programmers are responsible for software quality - quality in their own work, quality in the products that incorporate their work, and quality at the interfaces between components. Quality has never been and will never be tested in. The responsibility is both moral and professional." (Boris Beizer, "Software Testing Techniques", 1990)

"A problem with this 'waterfall' approach is that there will then be no user interface to test with real users until this last possible moment, since the 'intermediate work products' do not explicitly separate out the user interface in a prototype with which users can interact. Experience also shows that it is not possible to involve the users in the design process by showing them abstract specifications documents, since they will not understand them nearly as well as concrete prototypes." (Jakob Nielsen, "Usability Engineering", 1993)

"One should not start full-scale implementation efforts based on early user interface designs. Instead, early usability evaluation can be based on prototypes of the final systems that can be developed much faster and much more cheaply, and which can thus be changed many times until a better understanding of the user interface design has been achieved." (Jakob Nielsen, "Usability Engineering", 1993)

"Scenarios are an especially cheap kind of prototype. […] Scenarios are the ultimate reduction of both the level of functionality and of the number of features: They can only simulate the user interface as long as a test user follows a previously planned path. […] Scenarios are the ultimate minimalist prototype in that they describe a single interaction session without any flexibility for the user. As such, they combine the limitations of both horizontal prototypes (users cannot interact with real data) and vertical prototypes (users cannot move freely through the system)." (Jakob Nielsen, "Usability Engineering", 1993)

"The difference between standards and guidelines is that a standard specifies how the interface should appear to the user, whereas a set of guidelines provides advice about the usability characteristics of the interface." (Jakob Nielsen, "Usability Engineering", 1993)

"Users often do not know what is good for them. […] Users have a very hard time predicting how they will interact with potential future systems with which they have no experience. […] Furthermore, users will often have divergent opinions when asked about details of user interface design." (Jakob Nielsen, "Usability Engineering", 1993)

"As the least conscious layer of the user experience, the conceptual model has the paradoxical quality of also having the most impact on usability. If an appropriate conceptual model is faithfully represented throughout the interface, after users recognize and internalize the model, they will have a fundamental understanding of what the application does and how to operate it." (Bob Baxley, "Making the Web Work: Designing Effective Web Applications", 2002)

"Modularity, an approach that separates a large system into simpler parts that are individually designed and operated, incorrectly assumes that complex system behavior can essentially be reduced to the sum of its parts. A planned decomposition of a system into modules works well for systems that are not too complex. […] However, as systems become more complex, this approach forces engineers to devote increasing attention to designing the interfaces between parts, eventually causing the process to break down."  (Yaneer Bar-Yam, "Making Things Work: Solving Complex Problems in a Complex World", 2004)

"On small, informal projects, a lot of design is done while the programmer sits at the keyboard. 'Design' might be just writing a class interface in pseudocode before writing the details. It might be drawing diagrams of a few class relationships before coding them. It might be asking another programmer which design pattern seems like a better choice. Regardless of how it’s done, small projects benefit from careful design just as larger projects do, and recognizing design as an explicit activity maximizes the benefit you will receive from it." (Steve C McConnell, "Code Complete: A Practical Handbook of Software Construction" 2nd Ed., 2004)

"Enterprise architecture is the organizing logic for business processes and IT infrastructure reflecting the integration and standardization requirements of a company's operation model. […] The key to effective enterprise architecture is to identify the processes, data, technology, and customer interfaces that take the operating model from vision to reality." (Jeanne W Ross et al, "Enterprise architecture as strategy: creating a foundation for business", 2006)

"An abstraction is not a module, or an interface, class, or method; it is a structure, pure and simple - an idea reduced to its essential form. Since the same idea can be reduced to different forms, abstractions are always, in a sense, inventions, even if the ideas they reduce existed before in the world outside the software. The best abstractions, however, capture their underlying ideas so naturally and convincingly that they seem more like discoveries." (Daniel Jackson, "Software Abstractions", 2006)

"Software is built on abstractions. Pick the right ones, and programming will flow naturally from design; modules will have small and simple interfaces; and new functionality will more likely fit in without extensive reorganization […] Pick the wrong ones, and programming will be a series of nasty surprises: interfaces will become baroque and clumsy as they are forced to accommodate unanticipated interactions, and even the simplest of changes will be hard to make." (Daniel Jackson, "Software Abstractions", 2006)

"We tend to form mental models that are simpler than reality; so if we create represented models that are simpler than the actual implementation model, we help the user achieve a better understanding. […] Understanding how software actually works always helps someone to use it, but this understanding usually comes at a significant cost. One of the most significant ways in which computers can assist human beings is by putting a simple face on complex processes and situations. As a result, user interfaces that are consistent with users’ mental models are vastly superior to those that are merely reflections of the implementation model." (Alan Cooper et al,  "About Face 3: The Essentials of Interaction Design", 2007)

"Structural patterns describe how classes and objects can be combined to form larger structures. Patterns for classes describe how inheritance can be used to provide more useful program interfaces. Patterns for objects describe how objects can be composed into larger structures using object composition." (Junji Nakano et al, "Programming Statistical Data Visualization in the Java Language" [in "Handbook of Data Visualization"], 2008)

"Making interfaces hard to use incorrectly requires two things. First, you must anticipate errors users might make and find ways to prevent them. Second, you must observe how an interface is misused during early release and modify the interface - yes, modify the interface! - to prevent such errors. The best way to prevent incorrect use is to make such use impossible. If users keep wanting to undo an irrevocable action, try to make the action revocable. If they keep passing the wrong value to an API, do your best to modify the API to take the values that users want to pass." (Scott Meyers, [in Kevlin Henney’s "97 Things Every Programmer Should Know", 2010])

"More generally, each unit of code, from a block to a library, should have a narrow interface. Less communication reduces the reasoning required. This means that getters that return internal state are a liability - don’t ask an object for information to work with. Instead, ask the object to do the work with the information it already has. In other words, encapsulation is all - and only - about narrow interfaces." (Yechiel Kimchi [in Kevlin Henney’s "97 Things Every Programmer Should Know", 2010])

"Good architecture provides good interfaces that separate the shear layers of its implementation: a necessity for evolution and maintenance. Class-oriented programming puts both data evolution and method evolution in the same shear layer: the class. Data tend to remain fairly stable over time, while methods change regularly to support new services and system operations. The tension in these rates of change stresses the design." (James O Coplien & Trygve Reenskaug, "The DCI Paradigm: Taking Object Orientation into the Architecture World", 2014)

"When an engineer refactors the internals of a system without modifying its interface, whether for performance, clarity, or any other reason, the system’s tests shouldn’t need to change. The role of tests in this case is to ensure that the refactoring didn’t change the system’s behavior. Tests that need to be changed during a refactoring indicate that either the change is affecting the system’s behavior and isn’t a pure refactoring, or that the tests were not written at an appropriate level of abstraction." (Titus Winters, "Software Engineering at Google: Lessons Learned from Programming Over Time", 2020)

06 April 2007

🌁Software Engineering: Interface (Definitions)

"(1) A shared boundary across which information is passed. (2) A hardware or software component that connects two or more other components for the purpose of passing information from one to the other. (3) To connect two or more components for the purpose of passing information from one to the other. (4) To serve as a connecting or connected component as in (2)."  (IEEE, "IEEE Standard Glossary of Software Engineering Terminology", 1990)

"(1) A shared boundary between two or more hardware or software components that conveys power and/or information from one to the other (2) To connect two or more components for the purpose of passing power and/or information from one to the other." (Richard D Stutzke, "Estimating Software-Intensive Systems: Projects, Products, and Processes", 2005)

"An interface exists between different systems or between systems and networks when considered within the context of computer technology. An interface can also refer to the way in which people interact with a computer or other type of device (a user interface or graphical user interface). An interface can also have an organizational connotation where one organization works closely with (interfaces with) another. There are other definitions based on the industry context. However, these may be most common to product managers." (Steven Haines, "The Product Manager's Desk Reference", 2008)

"The connection between two components of a system. Analysis is concerned with the data content of an interface, and design is concerned with the behavior and appearance of the interface." (James Robertson et al, "Complete Systems Analysis: The Workbook, the Textbook, the Answers", 2013)

"Interconnection and interrelation between, for example, people, systems, devices, applications, and so on." (Gilbert Raymond & Philippe Desfray, "Modeling Enterprise Architecture with TOGAF", 2014)

07 January 2007

🌁Software Engineering: Design (Definitions)

(1) The process of defining the architecture, components, interfaces, and other characteristics of a system or component. (2) The result of the process in (1)."  (IEEE," IEEE Standard Glossary of Software Engineering Terminology", 1990)

"A process that uses the products of analysis to produce a specification for implementing a system. A logical description of how a system will work." (Craig Larman, "Applying UML and Patterns", 2004)

"The activity of identifying and defining the architecture, components, interfaces, and attributes of a system or product. See also architectural design. (2) The result of the process in (1)." (Richard D Stutzke, "Estimating Software-Intensive Systems: Projects, Products, and Processes", 2005)

"Analysis discovers what needs to be done. Design figures out how what has been analyzed, can and should be done." (Gavin Powell, "Beginning Database Design", 2006)

"The act of crafting a technological solution to fit the requirements, within the constraints." (Suzanne Robertson & James Robertson, "Mastering the Requirements Process" 2nd Ed, 2006)

"The process of optimizing an analysis model through the selection of design technologies, decisions, and patterns." (Bruce P Douglass, "Real-Time Agility: The Harmony/ESW Method for Real-Time and Embedded Systems Development", 2009)

"1.A deliberate, purposeful plan, layout, delineation, arrangement, and specification of the component parts and interfaces of a product or system. A logical design is an abstract design for fulfilling requirements without consideration for physical constraints. A physical design considers the requirements along with physical constraints. 2.Verb. To conceive, plan, define, arrange, and specify a product or system." (DAMA International, "The DAMA Dictionary of Data Management", 2011)

"A plan or outline to accomplish goals and purpose based on evidence and analysis. Degree of detail depends on the situation, such as prototypes and storyboards." (Joan C Dessinger, "Fundamentals of Performance Improvement" 3rd Ed, 2012)

"The process of defining how a system will be implemented; the objective is to use the available technology to implement the essential requirements so that the implemented system looks as much like the essential system, and hence the problem, as possible." (James Robertson et al, "Complete Systems Analysis: The Workbook, the Textbook, the Answers", 2013)

"Design is an iterative process and the goal is to describe the system architecture that will satisfy the functional and non-functional requirements. It involves describing the system at a number of different levels of abstraction, with the designer starting off with an informal picture of the design that is then refined by adding more information." (Gerard O’Regan, "Concise Guide to Software Engineering: From Fundamentals to Application Methods", 2017)

"Activity or process that identifies requirements and then defines a solution that is able to meet these requirements" (ITIL)

07 January 2006

♯OOP: Interface (Definitions)

"A contract that specifies the members a class or struct can implement to receive generic services for that type." (Jesse Liberty, "Programming C#" 2nd Ed., 2002)

"In Java, an interface is similar to a class definition, except that no detailed implementation of methods is provided. A class that implements an interface must provide the code to implement the methods. You can think of an interface as defining a contract between the calling method and the class that implements the interface." (Marcus Green & Bill Brogden, "Java 2™ Programmer Exam Cram™ 2 (Exam CX-310-035)", 2003)

"A set of signatures of public operations." (Craig Larman, "Applying UML and Patterns", 2004)

"A defined set of properties, methods, and collections that form a logical grouping of behaviors and data. Classes are defined by the interfaces that they implement. An interface can be implemented by many different classes." (Jim Joseph et al, "Microsoft SQL Server 2008 Reporting Services Unleashed", 2009)

"The specification of the means by which services can be invoked and data can be manipulated across an encapsulation boundary (e.g., class)." (Bruce P Douglass, "Real-Time Agility", 2009)

"The externally visible definition of the operations permitted on an application component." (David Lyle & John G Schmidt, "Lean Integration", 2010)

"Defines a set of members that a class can provide." (Rod Stephens, "Start Here! Fundamentals of Microsoft .NET Programming", 2011)

"Defines public properties, methods, and events that a class must provide to satisfy the interface." (Rod Stephens, "Stephens' Visual Basic Programming 24-Hour Trainer", 2011)

"A defined set of properties, methods, and collections that form a logical grouping of behaviors and data." (Microsoft, "SQL Server 2012 Glossary", 2012)

"The services a piece of code promises to provide forever, in contrast to its implementation, which it should feel free to change whenever it likes." (Jon Orwant et al, "Programming Perl" 4th Ed., 2012)

"A keyword used to declare an interface." (Daniel Leuck et al, "Learning Java" 5th Ed., 2020)

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