BCS Lovelace Lecture 2009

The Sins of IT Projects and why they can fail.

The 2008 Lovelace Medal was awarded to Dr Tony Storey, IBM Fellow and Distinguished Engineer. Maurice Perks, IBM Fellow presented the Lecture on his behalf. In this lecture IBM Fellow Maurice Perks related some of the technical IT experiences that he has encountered during forty years of dealing with complex IT projects within large enterprises that cover finance, manufacturing and government industry sectors. He focused on why IT projects, especially large ones, can have a high risk of failure due to a number of technical factors and how there are recurring themes. He explained how we can often de-risk large IT projects when we understand these factors now that our own industry has matured. To do this we have to understand how the continuing technology developments of our fast-moving industry can be harnessed within the bounds of acceptable risks and probabilities of success. He discussed such challenges as the continuous changes that IT projects face from several quarters, the never-ending search for perfect application code that does not need testing, and some heroic attempts to produce home produced middleware that can turn a traditional commercial enterprise into a budding IT software house. The lecture will not have all the answers but will pose a few key questions that can be asked at the right project moments.

Hello, this is a test.

BCS Lovelace Lecture 2009

The Sins of IT Projects and why they can fail.

The 2008 Lovelace Medal was awarded to Dr Tony Storey, IBM Fellow and Distinguished Engineer. Maurice Perks, IBM Fellow presented the Lecture on his behalf. In this lecture IBM Fellow Maurice Perks related some of the technical IT experiences that he has encountered during forty years of dealing with complex IT projects within large enterprises that cover finance, manufacturing and government industry sectors. He focused on why IT projects, especially large ones, can have a high risk of failure due to a number of technical factors and how there are recurring themes. He explained how we can often de-risk large IT projects when we understand these factors now that our own industry has matured. To do this we have to understand how the continuing technology developments of our fast-moving industry can be harnessed within the bounds of acceptable risks and probabilities of success. He discussed such challenges as the continuous changes that IT projects face from several quarters, the never-ending search for perfect application code that does not need testing, and some heroic attempts to produce home produced middleware that can turn a traditional commercial enterprise into a budding IT software house. The lecture will not have all the answers but will pose a few key questions that can be asked at the right project moments.

Software failures can be sorted into two groups: Those that cause the software to crash, and those that result in the software hanging. Although crashes are frustrating, we at lease know we must take drastic action (e.g. rebooting).

Hangs are psychologically more difficult, as there is always the lingering possibility that we are simply too impatient and should wait a while longer for the machineto respond.

Software failures can be sorted into two groups: Those that cause the software to crash, and those that result in the software hanging. Although crashes are frustrating, we at lease know we must take drastic action (e.g. rebooting). Hangs are psychologically more difficult, as there is always the lingering possibility that we are simply too impatient and should wait a while longer for the machineto respond.

Software failures can be sorted into two groups: Those that cause the software to crash, and those that result in the software hanging. Although crashes are frustrating, we at lease know we must take drastic action (e.g. rebooting). Hangs are psychologically more difficult, as there is always the lingering possibility that we are simply too impatient and should wait a while longer for the machineto respond.

Software failures can be sorted into two groups: Those that cause the software to crash, and those that result in the software hanging. Although crashes are frustrating, we at lease know we

Software failures can be sorted into two groups: Those that cause the software to crash, and those that result in the software hanging. Although crashes are frustrating, we at lease know we must take drastic action (e.g. rebooting). Hangs are psychologically more difficult, as there is always the lingering possibility that we are simply too impatient and should wait a while longer for the machineto respond.

Software failures can be sorted into two groups: Those that cause the software to crash, and those that result in the software hanging. Although crashes are frustrating, we at lease know we must take drastic action (e.g. rebooting). Hangs are psychologically more difficult, as there is always the lingering possibility that we are simply too impatient and should wait a while longer for the machineto respond.

Software failures can be sorted into two groups: Those that cause the software to crash, and those that result in the software hanging. Although crashes are frustrating, we at lease know we must take drastic action (e.g. rebooting). Hangs are psychologically more difficult, as there is always the lingering possibility that we are simply too impatient and should wait a while longer for the machineto respond.

Software failures can be sorted into two groups: Those that cause the software to crash, and those that result in the software hanging. Although crashes are frustrating, we at lease know we

"What will a companionable computational agent be like?" Professor Yorick Wilks, Oxford Internet Institute at Balliol College.

The lecture begins by looking at the state of the art in modeling realistic conversation with computers over the last 40 years. I then move on to ask what we would want in a long-term conversational agent that was designed for a long-term relationship with a user, rather than the carrying out of a single brief task, like buying a railway ticket. Such an agent I shall call "companionable": I shall distinguish several functions for such agents, but the feature they share will be that, in some definable sense, a computer Companion knows a great deal about its owner and can use that information.

By way of illustration, the lecture describes the functionality and system modules of a Senior Companion (SC), one of two initial prototypes built in the first two years of the EC Companions project. The SC provides a multimodal interface for eliciting and retrieving personal information from the elderly user through a conversation about their photographs. The Companion, through conversation, elicits life memories, often prompted by discussion of their photographs. The demonstration is primitive but plausible and one of its key features is an ability to break out of the standard AI constraint on very limit pre-programmed knowledge worlds into a wider, unbounded world of knowledge in the Internet by capturing web knowledge in real time, again by Information Extraction methods. The lecture finally discusses the prospects for machine learning in the conversational modeling field and progress to date on incorporating notions of emotion into AI systems.

"What will a companionable computational agent be like?" Professor Yorick Wilks, Oxford Internet Institute at Balliol College.

The lecture begins by looking at the state of the art in modeling realistic conversation with computers over the last 40 years. I then move on to ask what we would want in a long-term conversational agent that was designed for a long-term relationship with a user, rather than the carrying out of a single brief task, like buying a railway ticket. Such an agent I shall call "companionable": I shall distinguish several functions for such agents, but the feature they share will be that, in some definable sense, a computer Companion knows a great deal about its owner and can use that information.

By way of illustration, the lecture describes the functionality and system modules of a Senior Companion (SC), one of two initial prototypes built in the first two years of the EC Companions project. The SC provides a multimodal interface for eliciting and retrieving personal information from the elderly user through a conversation about their photographs. The Companion, through conversation, elicits life memories, often prompted by discussion of their photographs. The demonstration is primitive but plausible and one of its key features is an ability to break out of the standard AI constraint on very limit pre-programmed knowledge worlds into a wider, unbounded world of knowledge in the Internet by capturing web knowledge in real time, again by Information Extraction methods. The lecture finally discusses the prospects for machine learning in the conversational modeling field and progress to date on incorporating notions of emotion into AI systems.