- Email: [email protected]
Potential applications of artificial intelligence in telecommunications
Technova~~on, 14(7) (1994) 431-435
Potential applications of artificial intelligence in telecommunications Alexander Chablo Flat 3, 23 Goulden
Road,
Withington,
Manchester
M20 4ZE, UK
Abstract This paper discusses the potential applications within telecommunications of the whole range of artificial intelligence technologies (i.e., expert systems, natural language understanding, speech recognition and understanding, machine translation, visual recognition and analysis, and robotics). Potential applications are discussed in several areas of a telecommunications company’s operation, for example engineering, computing, sales and marketing, personnel, finance, and products.
1.
What is artificial
intelligence?
2.1.
The definition of artificial intelligence (AI) used in this paper is that AI is the attempt to make machines mimic reasoning and actions which, if performed by a human, would require intelligence. AI includes several technologies, expert systems, natural language understanding, speech recognition and understanding, machine translation, visual recognition and analysis, and robotics.
2. Potential areas of application expert systems
of
An expert .system is a computer program with a knowledge base of expertise capable of reasoning at the level of an expert in some domain. Expert systems have potential applications in several areas of a telecommunications company’s operation, for example engineering, computing, sales and marketing, personnel, finance, and products.
Technovation
Vol. 14 No. 7
Engineering
Expert systems will have uses in diagnosing faults on telephone exchanges and customers’ telecommunications equipment. The DMSl expert system was developed by Bell Canada for field technicians repairing DMSl switches. It has about 600 rules [l]. Building and using expert systems as the engineering documentation of a product, e.g. a private switchboard or multiplexor, will be useful in speeding up product introduction. Such expert systems would encode installation, configuration, test and fault diagnosis information. The training of an adequate number of engineers to install and maintain products can be a bottleneck in product installation. Expert systems will also be important in preserving and encoding rare engineering expertise. For instance, several of BTI’s satellite earthstations contain unique equipment. A great deal of an engineer’s time is spent in training to ensure adequate engineering cover in the event of illness,
0166-4972/94/US$O7.00
0
1994 Elsevier Science Ltd
431
A. Chabio
holidays, and employment transfers including promotion. Also, in many countries, many analogue switches are still in use and, as analogue switches are replaced by digital exchanges, there is a decreasing number of engineers with the operating SMART and maintenance skills required. (Switching Maintenance Analysis and Repair Tool) is an expert system preserving analogue engineering expertise [2]. Network management expert systems will advise on the best use of circuits, avoiding congestion and reducing costs in the case of international calls. Planning and project management systems will assist in scheduling deployment of engineers for repair and installation tasks. Regarding network planning, an attempt has been made by Costa, Climaco and Craveirinha [3] to integrate AI techniques to improve a heuristicbased OR model for rural telephone network planning. Also, an expert system, Seteli, uses information on investment policies and tariff policies to project future demands so as to assist the planning of telecommunications systems [4]. The US Defence Communications Agency has a European Theatre Command Communications Architecture with, at present, 700 communications nodes, 1200 connecting links and 800 separate network users. There are more than 10000 possible upgrades for this network. XTEL is an expert system which can design such military networks. It creates files of site and link information. A vulnerability assessment tool then assesses enemy military threats, and computes survivability values for sites and link. New network designs can be produced by XTEL if there is a change in assumptions or design philosophy. XTEL is currently used to design telecommunications architecture [5]. Expert systems will play a role in training engineers. SOPHIE (Sophisticated Instructional Electronic Environment Teaching for Troubleshooting) is a project initiated by the US Air Force [6].
432
2.2.
Computing
AI will have an effect in increasing programmers’ productivity. This is because AI programming languages are more English-like than conventional programming languages. Another major impact of AI will be in the production of intelligent software support systems. These will assist the programmer in keeping track of the structure of the programme and highlighting errors. There are already several knowledge engineering assistants commercially available to assist in the process of knowledge acquisition and representation. In British Telecom (BT) a Software Engineering Navigator (SEAN) has been Architecture developed to give guidance to recommended procedures for software procurement, maintenance and development within BT. This attempts to overcome the difficulties of keeping up with best software techniques, and evaluation of available options, occasioned by the rapid rate of change in software technology.
2.3.
Sales and marketing
Expert systems will be of use in advising sales staff on the most appropriate telecommunications system that can meet a customer’s needs. These can help to structure the interview between sales staff and customer and ensure accuracy and consistency of information provided to customers. The Service Definition Expert System [7] is just such a prototype expert system to support telecommunicatons sales proposals. ENS [8] is a prototype developed by BNR and Bell Canada for sales representatives to produce network configurations and pricing information. Expert systems will help in sales forecasting, and in sales target setting and monitoring, for managers of sales forces and marketeers. Expert systems will be of use in advising and configuring specialist equipment such as multiplexors. Since 1980 Digital has been using XCON in supporting manufacture, and the order verification processes to configure individual computers to
Technovation
Vol. 14 No. 7
Potentiat applications
customer requirements. It may be that one day customers will dial up an intelligent database, find out the nature and cost of the equipment recommended for their telecommunications problem, and place an order electroni~lly. This will release office-based sales staff to carry out a more proactive telephone sales role rather than a passive order-taking role. 2.4.
Personnel
Personnel work can be divided into two kinds: services to staff, and management of staff. In services provided to staff, expert systems will find applications in systems to advise on training, tax and pensions. In the administration of staff, applications will include automatic sifting of initial recruitment and giving advice on discipline rules. 2.5.
Finance
Finance can broadly be divided into two areas. Firstly, finance involves the day-to-day monitoring of cash inflows and outflows. Conventional programmes are already taking over most of this burden. Secondly, finance involves the interpretation of accounts. This is already becoming a general management function, and with expert systems this knowledge will become more easily decentralized. According to Van de Brug and Orciuch [9], the computer company Digital has a Finance Accounting Navigator. This system overcomes the problem of the shortage of financial analysts by carrying out the task of analysing cost centre accounts. 2.6.
Information
systems
and databases
Info~ation centres providing commercial information to a company have three aspects to their operations, Firstly, they aim to enable users of the information to help themselves more easily. Expert systems will be more user friendly, and will guide the user more directly to the appropriate database,
Technovation
Vol. 14 No. 7
of artificial
intelligence
in teiecommunications
then to the required item of data. This will be facilitated by intelligent front-ends to databases. Secondly, information centres have to provide information to clients. This will be more speedily accessed by the info~ation centre on intelligent databases. Automatic summarizing, abstracting and keywording systems, incorporating AI techniques, will speed up the process of building up in-house databases. Thirdly, information centres have to accumulate, then catalogue and classify information. Classification expert systems will assist with this task. 2.7.
Products
BT supplies private circuit networks to large organizations. Call management systems are sold to customers to help with network management. These systems give information on circuit utilization, faults, incoming calls. This information is used to determine the need for, or cost effectiveness of, additional private circuits, and the adequacy of switchboard operator cover. AI knowledgebased techniques may usefully be embedded in call management systems to increase their use.
Natural language under~anding automatic text generation
3.
and
An application for automatic text generation (ATG) is in annotating statistics, e.g. itemized bills for customers, and annotating fault reports from telephone exchanges. Another application of natural language understanding and ATG is in summarization, for automatic generation of summaries and abstracts for entry into databases and catalogues.
4.
Speech
recognition
Three important problems to be overcome are: the understanding of continuous speech; speakerindependent speech recognition; and removal of background noise from speech analysis.
433
A. Chablo
The obvious application for speech understanding is the provision of databases and info~ation services over the telephone, e.g. train timetables. BT has worked to produce a demonstration model of a voice-interrogatable database called VODIS, which stands for Voice Operated Database Inquiry System. At the moment speech recognition systems can be trained to recognize words spoken separately by a single speaker. Such systems will be of use in warehouses, where records need to be kept by those whose hands are often full. Other applications will be found in credit card verification by phone, and phone banking, where voice patterns will be matched to a customer’s records to verify identity.
5.
Machine translation
Machine translation will be of use in automatically translating databases, originally in a foreign language, which cover limited and specialized areas of knowledge, e.g. technical databases and weather reports. The Japanese are working on a long-term project to automatically translate Japanese speech into English, and vice versa, during telephone conversations.
6.
Robotics
There are several potential applications of robots in telecommunications companies. Robots are currently used to recover undersea tele~mmunications cables for repair. BT currently has an undersea craft called Seadog. Seadog can bury cables, and inspect, recover and rebury cables during maintenance. The craft is controlled by an umbilical lifeline connected to a ship. Seadog operates at depths of up to 300 m. It has a general purpose manipulator, three video cameras, a high definition camera on the manipulator arm, and a 35 mm still camera. Cables are located and tracked using an active magnetic cable sensing system.
434
The craft also has depth, pitch and roll sensors. In addition, an acoustic navigation system locates Seadog with respect to the ship, and a further acoustic system enables Seadog to avoid obstacles. Improvements in sensing and planning will mean that such undersea robots will be able to operate increasingly independently. Developments in robot manipulators will lead to more flexible deployment of undersea robots. These deep-sea conditions are of course environments in which it is impossible for humans to operate. Robots will also find applications in integrated circuit manufacturing, in clean rooms of chip manufactu~ng facilities. Human workers, unlike robots, are at risk from the ions in the atmosphere of a clean room; and humans also give off dust which lowers the productivity of the manufacturing process.
7.
Vision recognition
and analysis
Vision systems will have applications in facial recognition for security access to buildings. Visual AI technology should also be useful in reducing the telecommunications circuit transmission capacity taken up by videophone and video-conferencing systems. Such systems currently gradually transmit and build up a whole scene, and then subsequently transmit information only on changes in the picture. Little movement is entailed by facial and body movements during videophone and videoconferencing transmissions. Knowledge-based systems may enable further reductions in the amount of information required to transmit videophone or videoconferencing images, e.g. by relating words spoken to mouth movements and the shapes required to produce them. The BBC and Snell and Wilcox have produced a system called Gazelle aimed at making slow motion replays less jerky. Gazelle analyses motion in TV frames and creates extra frames to fill in the gaps (see New Scientist, 18 July 1992). Gazelle analyses such pictures of a motion sequence and detects which objects are moving, where they are
Technovation
Vol. 14 No. 7
Potential
applications
going in the picture and at what speed and angle. Gazelle uses military image-processing chips.
References 1 R.D. Bell, Diagnostic and administrative expert systems at Bell Canada Network Services. In: C.Y. Suen and R. Shinghal (eds.), Operational Expert Systems in Canada. Pergamon Press, Oxford, 1991. 2 M.T. Sutter, The SMART project: an approach to expert system integration and evaluation in the BOCs. In: Internat&al Conference on Communications (ICC’ 86), pp. 1230-1232. IEEE, Toronto, 1986. 3.P. Costa, J.N. Climaco and J.F. Craveirinha, A tentative approach to integrate AI techniques to improve a heuristic-based OR model for rural telephone network planning. In: Knowledge Data and Computer Assisted Decisions: Proceedings of the NATO Advanced Research Workshop on Data, Expert Knowledge and Decision, Hamburg, Germany, 3-5 September, 1989.
A. Salo and R.P. Hamalainen, Seteli: the strategy expert for telecommunication investments. IEEE Expert, 5(5) (1990) 14-22. J.L. Feinstein, F. Siems, J. Popolizio, D. Bailey and A. Wang, XTEL: an expert system for designing theaterwide telecommunications architectures. In: J. Liebowitz, Expert System Applications to Telecommunications. J. Wiley & Sons, New York, 1988. J.D. Fletcher and J. Psotka, Intelligent training systems for maintenance. Signal (June 1986). P. Mehotra, S. Erfani, Y.P. Lee, and H. Sachar, Design of an on-line telecommunications service definition tool based on expert system technology. In: R.V. Milekkileni (ed.), Proceedings of the IEEE
Technovation
Vol. 14 No. 7
of artificial
intelligence
in telecommunications
Network Operations and Management
Symposium.
IEEE, New York, 1988. 8 I. Ferguson, J. Rabie, J. Kennedy and R. Peacocke, A knowledge-based sales assistant for data communications networks. In: D.J. Sassa (ed.), International Communications Conference Z987. IEEE, New York. 9 Van de Brug and Orciuch, Successful corporate strategy. In: I.M. Graham and R.W. Milne (eds.), Research and Development
in Expert Systems VIII.
1991. I. Thurlow, C. Sharpe and S. 10 A. Drakeford, Jeyasingh, Intelligent guidance to software engineering information. BT Technology Journal, lO(2) (April 1992). 11 P. Grogono, A. Preece, R. Shinghal and C.Y. Suen, A survey of evaluation techniques used for expert systems in telecommunications. Expert Systems with Applications.
5( 1992) 395-401,
12 J. Liebowitz, Expert System Applications to Telecommunications. J Wiley & Sons, New York, 1988. 13 R. Marsh, Automatic text generation. British Telecorn Technology Journal, 6(4) (October, 1988). 14 J.G. Wilpon, R.P. Mikkilineni, D.B. Roe and S. Gokcen, Speech recognition: from the laboratory to the real world. AT&T Technical Journal, (September-October 1990). Alexander Chablo obtained his BA degree in Chemistry from Oxford University in 1978. After research at UMIST in quantum chemistry, he joined British Telecom as a manager in 1981. In BT he has worked on the computer support of System X digital exchanges; in international relations with British Telecom International; with national account management; as BT’s Corporate Artificial Intelligence Liaison Officer; and in strategy and planning in the Computer Services Division of UK Communications. In 1988, having left BT, Chablo decided to take up social anthropology. He is a Fellow of the Royal Anthropological Institute. His research interests include the organizational effects of technological change, and corporate cultures. He is an independent consultant.
435
Potential applications of artificial intelligence in telecommunications Alexander Chablo Flat 3, 23 Goulden
Road,
Withington,
Manchester
M20 4ZE, UK
Abstract This paper discusses the potential applications within telecommunications of the whole range of artificial intelligence technologies (i.e., expert systems, natural language understanding, speech recognition and understanding, machine translation, visual recognition and analysis, and robotics). Potential applications are discussed in several areas of a telecommunications company’s operation, for example engineering, computing, sales and marketing, personnel, finance, and products.
1.
What is artificial
intelligence?
2.1.
The definition of artificial intelligence (AI) used in this paper is that AI is the attempt to make machines mimic reasoning and actions which, if performed by a human, would require intelligence. AI includes several technologies, expert systems, natural language understanding, speech recognition and understanding, machine translation, visual recognition and analysis, and robotics.
2. Potential areas of application expert systems
of
An expert .system is a computer program with a knowledge base of expertise capable of reasoning at the level of an expert in some domain. Expert systems have potential applications in several areas of a telecommunications company’s operation, for example engineering, computing, sales and marketing, personnel, finance, and products.
Technovation
Vol. 14 No. 7
Engineering
Expert systems will have uses in diagnosing faults on telephone exchanges and customers’ telecommunications equipment. The DMSl expert system was developed by Bell Canada for field technicians repairing DMSl switches. It has about 600 rules [l]. Building and using expert systems as the engineering documentation of a product, e.g. a private switchboard or multiplexor, will be useful in speeding up product introduction. Such expert systems would encode installation, configuration, test and fault diagnosis information. The training of an adequate number of engineers to install and maintain products can be a bottleneck in product installation. Expert systems will also be important in preserving and encoding rare engineering expertise. For instance, several of BTI’s satellite earthstations contain unique equipment. A great deal of an engineer’s time is spent in training to ensure adequate engineering cover in the event of illness,
0166-4972/94/US$O7.00
0
1994 Elsevier Science Ltd
431
A. Chabio
holidays, and employment transfers including promotion. Also, in many countries, many analogue switches are still in use and, as analogue switches are replaced by digital exchanges, there is a decreasing number of engineers with the operating SMART and maintenance skills required. (Switching Maintenance Analysis and Repair Tool) is an expert system preserving analogue engineering expertise [2]. Network management expert systems will advise on the best use of circuits, avoiding congestion and reducing costs in the case of international calls. Planning and project management systems will assist in scheduling deployment of engineers for repair and installation tasks. Regarding network planning, an attempt has been made by Costa, Climaco and Craveirinha [3] to integrate AI techniques to improve a heuristicbased OR model for rural telephone network planning. Also, an expert system, Seteli, uses information on investment policies and tariff policies to project future demands so as to assist the planning of telecommunications systems [4]. The US Defence Communications Agency has a European Theatre Command Communications Architecture with, at present, 700 communications nodes, 1200 connecting links and 800 separate network users. There are more than 10000 possible upgrades for this network. XTEL is an expert system which can design such military networks. It creates files of site and link information. A vulnerability assessment tool then assesses enemy military threats, and computes survivability values for sites and link. New network designs can be produced by XTEL if there is a change in assumptions or design philosophy. XTEL is currently used to design telecommunications architecture [5]. Expert systems will play a role in training engineers. SOPHIE (Sophisticated Instructional Electronic Environment Teaching for Troubleshooting) is a project initiated by the US Air Force [6].
432
2.2.
Computing
AI will have an effect in increasing programmers’ productivity. This is because AI programming languages are more English-like than conventional programming languages. Another major impact of AI will be in the production of intelligent software support systems. These will assist the programmer in keeping track of the structure of the programme and highlighting errors. There are already several knowledge engineering assistants commercially available to assist in the process of knowledge acquisition and representation. In British Telecom (BT) a Software Engineering Navigator (SEAN) has been Architecture developed to give guidance to recommended procedures for software procurement, maintenance and development within BT. This attempts to overcome the difficulties of keeping up with best software techniques, and evaluation of available options, occasioned by the rapid rate of change in software technology.
2.3.
Sales and marketing
Expert systems will be of use in advising sales staff on the most appropriate telecommunications system that can meet a customer’s needs. These can help to structure the interview between sales staff and customer and ensure accuracy and consistency of information provided to customers. The Service Definition Expert System [7] is just such a prototype expert system to support telecommunicatons sales proposals. ENS [8] is a prototype developed by BNR and Bell Canada for sales representatives to produce network configurations and pricing information. Expert systems will help in sales forecasting, and in sales target setting and monitoring, for managers of sales forces and marketeers. Expert systems will be of use in advising and configuring specialist equipment such as multiplexors. Since 1980 Digital has been using XCON in supporting manufacture, and the order verification processes to configure individual computers to
Technovation
Vol. 14 No. 7
Potentiat applications
customer requirements. It may be that one day customers will dial up an intelligent database, find out the nature and cost of the equipment recommended for their telecommunications problem, and place an order electroni~lly. This will release office-based sales staff to carry out a more proactive telephone sales role rather than a passive order-taking role. 2.4.
Personnel
Personnel work can be divided into two kinds: services to staff, and management of staff. In services provided to staff, expert systems will find applications in systems to advise on training, tax and pensions. In the administration of staff, applications will include automatic sifting of initial recruitment and giving advice on discipline rules. 2.5.
Finance
Finance can broadly be divided into two areas. Firstly, finance involves the day-to-day monitoring of cash inflows and outflows. Conventional programmes are already taking over most of this burden. Secondly, finance involves the interpretation of accounts. This is already becoming a general management function, and with expert systems this knowledge will become more easily decentralized. According to Van de Brug and Orciuch [9], the computer company Digital has a Finance Accounting Navigator. This system overcomes the problem of the shortage of financial analysts by carrying out the task of analysing cost centre accounts. 2.6.
Information
systems
and databases
Info~ation centres providing commercial information to a company have three aspects to their operations, Firstly, they aim to enable users of the information to help themselves more easily. Expert systems will be more user friendly, and will guide the user more directly to the appropriate database,
Technovation
Vol. 14 No. 7
of artificial
intelligence
in teiecommunications
then to the required item of data. This will be facilitated by intelligent front-ends to databases. Secondly, information centres have to provide information to clients. This will be more speedily accessed by the info~ation centre on intelligent databases. Automatic summarizing, abstracting and keywording systems, incorporating AI techniques, will speed up the process of building up in-house databases. Thirdly, information centres have to accumulate, then catalogue and classify information. Classification expert systems will assist with this task. 2.7.
Products
BT supplies private circuit networks to large organizations. Call management systems are sold to customers to help with network management. These systems give information on circuit utilization, faults, incoming calls. This information is used to determine the need for, or cost effectiveness of, additional private circuits, and the adequacy of switchboard operator cover. AI knowledgebased techniques may usefully be embedded in call management systems to increase their use.
Natural language under~anding automatic text generation
3.
and
An application for automatic text generation (ATG) is in annotating statistics, e.g. itemized bills for customers, and annotating fault reports from telephone exchanges. Another application of natural language understanding and ATG is in summarization, for automatic generation of summaries and abstracts for entry into databases and catalogues.
4.
Speech
recognition
Three important problems to be overcome are: the understanding of continuous speech; speakerindependent speech recognition; and removal of background noise from speech analysis.
433
A. Chablo
The obvious application for speech understanding is the provision of databases and info~ation services over the telephone, e.g. train timetables. BT has worked to produce a demonstration model of a voice-interrogatable database called VODIS, which stands for Voice Operated Database Inquiry System. At the moment speech recognition systems can be trained to recognize words spoken separately by a single speaker. Such systems will be of use in warehouses, where records need to be kept by those whose hands are often full. Other applications will be found in credit card verification by phone, and phone banking, where voice patterns will be matched to a customer’s records to verify identity.
5.
Machine translation
Machine translation will be of use in automatically translating databases, originally in a foreign language, which cover limited and specialized areas of knowledge, e.g. technical databases and weather reports. The Japanese are working on a long-term project to automatically translate Japanese speech into English, and vice versa, during telephone conversations.
6.
Robotics
There are several potential applications of robots in telecommunications companies. Robots are currently used to recover undersea tele~mmunications cables for repair. BT currently has an undersea craft called Seadog. Seadog can bury cables, and inspect, recover and rebury cables during maintenance. The craft is controlled by an umbilical lifeline connected to a ship. Seadog operates at depths of up to 300 m. It has a general purpose manipulator, three video cameras, a high definition camera on the manipulator arm, and a 35 mm still camera. Cables are located and tracked using an active magnetic cable sensing system.
434
The craft also has depth, pitch and roll sensors. In addition, an acoustic navigation system locates Seadog with respect to the ship, and a further acoustic system enables Seadog to avoid obstacles. Improvements in sensing and planning will mean that such undersea robots will be able to operate increasingly independently. Developments in robot manipulators will lead to more flexible deployment of undersea robots. These deep-sea conditions are of course environments in which it is impossible for humans to operate. Robots will also find applications in integrated circuit manufacturing, in clean rooms of chip manufactu~ng facilities. Human workers, unlike robots, are at risk from the ions in the atmosphere of a clean room; and humans also give off dust which lowers the productivity of the manufacturing process.
7.
Vision recognition
and analysis
Vision systems will have applications in facial recognition for security access to buildings. Visual AI technology should also be useful in reducing the telecommunications circuit transmission capacity taken up by videophone and video-conferencing systems. Such systems currently gradually transmit and build up a whole scene, and then subsequently transmit information only on changes in the picture. Little movement is entailed by facial and body movements during videophone and videoconferencing transmissions. Knowledge-based systems may enable further reductions in the amount of information required to transmit videophone or videoconferencing images, e.g. by relating words spoken to mouth movements and the shapes required to produce them. The BBC and Snell and Wilcox have produced a system called Gazelle aimed at making slow motion replays less jerky. Gazelle analyses motion in TV frames and creates extra frames to fill in the gaps (see New Scientist, 18 July 1992). Gazelle analyses such pictures of a motion sequence and detects which objects are moving, where they are
Technovation
Vol. 14 No. 7
Potential
applications
going in the picture and at what speed and angle. Gazelle uses military image-processing chips.
References 1 R.D. Bell, Diagnostic and administrative expert systems at Bell Canada Network Services. In: C.Y. Suen and R. Shinghal (eds.), Operational Expert Systems in Canada. Pergamon Press, Oxford, 1991. 2 M.T. Sutter, The SMART project: an approach to expert system integration and evaluation in the BOCs. In: Internat&al Conference on Communications (ICC’ 86), pp. 1230-1232. IEEE, Toronto, 1986. 3.P. Costa, J.N. Climaco and J.F. Craveirinha, A tentative approach to integrate AI techniques to improve a heuristic-based OR model for rural telephone network planning. In: Knowledge Data and Computer Assisted Decisions: Proceedings of the NATO Advanced Research Workshop on Data, Expert Knowledge and Decision, Hamburg, Germany, 3-5 September, 1989.
A. Salo and R.P. Hamalainen, Seteli: the strategy expert for telecommunication investments. IEEE Expert, 5(5) (1990) 14-22. J.L. Feinstein, F. Siems, J. Popolizio, D. Bailey and A. Wang, XTEL: an expert system for designing theaterwide telecommunications architectures. In: J. Liebowitz, Expert System Applications to Telecommunications. J. Wiley & Sons, New York, 1988. J.D. Fletcher and J. Psotka, Intelligent training systems for maintenance. Signal (June 1986). P. Mehotra, S. Erfani, Y.P. Lee, and H. Sachar, Design of an on-line telecommunications service definition tool based on expert system technology. In: R.V. Milekkileni (ed.), Proceedings of the IEEE
Technovation
Vol. 14 No. 7
of artificial
intelligence
in telecommunications
Network Operations and Management
Symposium.
IEEE, New York, 1988. 8 I. Ferguson, J. Rabie, J. Kennedy and R. Peacocke, A knowledge-based sales assistant for data communications networks. In: D.J. Sassa (ed.), International Communications Conference Z987. IEEE, New York. 9 Van de Brug and Orciuch, Successful corporate strategy. In: I.M. Graham and R.W. Milne (eds.), Research and Development
in Expert Systems VIII.
1991. I. Thurlow, C. Sharpe and S. 10 A. Drakeford, Jeyasingh, Intelligent guidance to software engineering information. BT Technology Journal, lO(2) (April 1992). 11 P. Grogono, A. Preece, R. Shinghal and C.Y. Suen, A survey of evaluation techniques used for expert systems in telecommunications. Expert Systems with Applications.
5( 1992) 395-401,
12 J. Liebowitz, Expert System Applications to Telecommunications. J Wiley & Sons, New York, 1988. 13 R. Marsh, Automatic text generation. British Telecorn Technology Journal, 6(4) (October, 1988). 14 J.G. Wilpon, R.P. Mikkilineni, D.B. Roe and S. Gokcen, Speech recognition: from the laboratory to the real world. AT&T Technical Journal, (September-October 1990). Alexander Chablo obtained his BA degree in Chemistry from Oxford University in 1978. After research at UMIST in quantum chemistry, he joined British Telecom as a manager in 1981. In BT he has worked on the computer support of System X digital exchanges; in international relations with British Telecom International; with national account management; as BT’s Corporate Artificial Intelligence Liaison Officer; and in strategy and planning in the Computer Services Division of UK Communications. In 1988, having left BT, Chablo decided to take up social anthropology. He is a Fellow of the Royal Anthropological Institute. His research interests include the organizational effects of technological change, and corporate cultures. He is an independent consultant.
435