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Book Reading #43 - Things That Make Us Smart

Reference Information
Title: Things That Make Us Smart: Defending Human Attributes in the Age of the Machine
Author: Donald Norman
Publisher: 1994 Basic Books

Chapter 1: A Human-Centered Technology

Summary:

The book begins by talking about problems with the new technology, how it is designed to aid convenience but often ends up confusing the users and becomes the cause of human errors. Norman suggests that the technology should be more human-centered, meaning getting information from human errors and their causes and incorporate the lessons into the technology designs.

He talks about two types of sciences:

• Hard sciences: requiring accurate measurements.
• Soft Sciences: based on observations, data collection and classification.

He also talks about two types of cognition:

• Experiential: when people react to events quickly and effortlessly - reflex actions.
• Reflective: when people think and make a decision before reacting.

Discussion:

Norman makes an excellent point when he says that the designs should be human centered rather than machine centered. It's indeed very important to understand human psychology and why human make mistakes to come up with intuitive designs and interfaces. Humans make mistakes and they are nowhere close to being ideal, knowing this fact can lead to intelligent designs.

Chapter 2: Experiencing the World

Summary:

In this chapter, he further discusses the different levels of cognition. He also talks about how these levels are applied differently in the real world scenarios. He then talks about how information about these two cognitive behaviors can be used effectively to strike a right balance between the two and incorporating this balance in technology design, thus leading to decrease in human errors.

He talks about three types of human learning:

• Accretion: The accumulations of knowledge, information and facts.
• Tuning: Gaining expertise at a task by repeatedly performing it.
• Restructuring:Forming of the right conceptual model behind whatever is learnt. This is the hardest part of learning.

Yet another term that he defines is Optimal Flow - the state in which the mind becomes fully engrossed and involved in the learning process.

Discussion:

After reading about four Donald Norman books, his style of writing is getting pretty monotonous and repetitive. The examples and pictures do make it interesting for a while before it again becomes monotonous. I understand that Norman comes from a technical background rather than from a literature background. He seems to have plenty of brilliant ideas, but the way he puts them does get repetitive.

Book Reading #44 - Why We Make Mistakes

Chapter 4: We Wear Rose Colored Glasses

Summary

Chapter 4 talks about how we remember what we want to remember rather what really happened. The author calls this as wearing rose colored glasses. We tend to remember our victories and forget about our losses. In one of the examples he mentions students remembering their grades to be higher than what they really were and gamblers remembering their wins. He states that this hindsight bias is a cause of many human errors.

Discussion

This chapter provided some really interesting examples that prove how we remember good things about ourselves to make ourselves feel better. I think our ego is one of the major contributing factor towards such behavior. One of the advantages of this behavior is positive attitude since remembering our losses doesn't really help us much.

Chapter 5: We Can Walk and Chew Gum - but Not Much Else

Summary:

Walking and chewing gum at the same time refers to multi-tasking. In this chapter, the author talks about human ability to multi-task. He mentions that we are not designed to multi-task, the maximum we can do is to chew gum and walk at the same time. But doing more than one things at a time has shown that both the tasks are done clumsily due lack of concentration. Some of the examples he mentions are car accidents due to texting while driving and the airplane crash that occurred because the pilot got too bugged by a minor issue, losing his focus on flying the plane. He also mentions a term called intentional blindness by which he means that if we have something else going in our minds, we tend to not see somethings that are right in front of our eyes.

Discussion:

The examples provided in this chapter prove that we should indulge ourselves in multiple simultaneous activities, especially when one of them can potentially harm us if not done well. This chapter explains us why texting or talking on phone while driving, using the car entertainment system or entering the location in the navigation system while driving can be extremely risky. An important lesson for the designers is to design a features that disallows the usage of such devices when it detects that the car is running so that the driver is forced to stop in order to use the devices.

Paper Reading #20: iSlideShow: a content-aware slideshow system

Reference Information

Title: iSlideshow: a Content-Aware Slideshow System
Authors: Jiajian Chen, Jun Xiao, Yuli Gao
Conference: IUI '10 Proceedings of the 15th international conference on Intelligent user interfaces

Summary

The authors present an intelligent photo slideshow system that automatically analyzes thematic information about the photo collection and utilizes such information to generate compositions and transitions in two modes: story-telling mode and person-highlighting mode. In the story-telling mode the system groups photos by a theme-based clustering algorithm and multiple photos in each theme cluster are seamlessly tiled on a slide. Multiple tiling layouts are generated for each theme cluster and the slideshow is animated by intra-cluster transitions. In the person-highlighting mode, the system first recognizes faces from photos and creates photo clusters for individuals. It then uses face areas as ROI (Regions of Interests) and creates various content-based transitions to highlight individuals in a cluster. With an emphasis on photo content, our system creates slideshows with more fluid, dynamic and meaningful structure compared to existing systems.

Figure 1.0 iSlideShow Interface

Discussion

Paper Reading 19: From documents to tasks: deriving user tasks from document usage patterns

Reference Information

Title: From Documents to Tasks: Deriving User Tasks from Document Usage Patterns
Authors: Oliver Brdiczka
Conference: IUI '10 Proceedings of the 15th international conference on Intelligent

Summary

A typical knowledge worker is involved in multiple tasks and switches frequently between them every work day. These frequent switches become expensive because each task switch requires some recovery time as well as the reconstitution of task context. First task management support systems have been proposed in recent years in order to assist the user during these switches. However, these systems still need a fairly big amount of investment from the user side in order to either learn to use or train such a system.

In order to reduce the necessary amount of training, this paper proposes a new approach for automatically estimating a user’s tasks from document interactions in an unsupervised manner. While most previous approaches to task detection look at the content of documents or window titles, which might raise confidentiality and privacy issues, our approach only requires document identifiers and the temporal switch history between them as input.

The prototype system monitors a user’s desktop activities and logs documents that have focus on the user’s desktop by attributing a unique identifier to each of these documents. Retrieved documents are filtered by their dwell times and a document similarity matrix is estimated based on document frequencies and switches. A spectral clustering algorithm then groups documents into tasks using the derived similarity matrix. The described prototype system has been evaluated on user data of 29 days from 10 different subjects in a corporation. Obtained results indicate that the approach is better than previous approaches that use content.

(Figure 1: Average precision, recall and F-measure with respect

to the number of user tasks)

Discussion

This paper was pretty technical. The authors, no doubt, comes from a highly technical background and his writing reflects this fact. However, I has taken the information storage and retrieval class last semester and I am quite familiar with the terms - clustering, F-measure, precision, recall, etc. that he uses in the paper. I think this system will be very useful since we switch between numerous tasks multiple times each day. Software like this would significantly improve work efficiently and reduce the downtime caused due to task switching.

Paper Reading 18: Evaluating the design of inclusive interfaces by simulation

Reference Information:

Title: Evaluating the Design of Inclusive Interfaces by Simulation.
Authors: Pradipta Biswas, Peter Robinson.
Conference: IUI '10 Proceedings of the 15th international conference on Intelligent user interfaces.

Summary:

The authors have developed a simulator to help with the design and evaluation of assistive interfaces. The simulator can predict possible interaction patterns when undertaking a task using a variety of input devices, and estimate the time to complete the task in the presence of different disabilities.

They have evaluated the simulator by considering a representative application being used by ablebodied, visually impaired and mobility impaired people. In the study that they conducted, they compared the simulator's predictions of the time it would take for people with impairment for performing various tasks vs. the time it would take for accomplishing these tasks for other users.

The simulator predicted task completion times for all three groups with statistically significant accuracy. The simulator also predicted the effects of different interface designs on task completion time accurately.

(Fig 1.0 Use of the simulator)

Discussion:

After reading this paper, I have an opinion that this is not a paper that presents a research idea or something that's new in the field. Instead, it presents results of the user study that the researchers conducted. They present their findings and this valuable piece of data can be used by other researchers to develop new applications and systems.