Emerging from the Dense, Digital Fog II
16. Januar 2023 19:05 Uhr | Dr. Ulrich Kampffmeyer | Permalink
Der Herausgeber des Buches „Tomorrow’s Jobs Today„, Rafael Moscatel, plant eine zweite, erweiterte Auflage des Buches aus dem Jahr 2021 (Paperback und elektronisch). Die erste Auflage verkaufte sich sehr gut. In dem Buch befand sich auch das Interview, das Dr. Kampffmeyer Rafael Moscatel im Herbst 2018 gegeben hatte. Das ursprüngliche Interview wurde gekürzt in das Buch übernommen. Ulrich Kampffmeyer wurde eingeladen, weitere Fragen für die 2. Auflage zu beantworten. Der damalige Beitrag aus dem Jahr 2018 mit den drei zusätzlichen Fragen und Antworten des Jahres 2022 ist hier zusammengefasst.
Wir freuen uns über Anregungen und Kommentare, besonders zu den Auswirkungen der Corona-Pandemie, den 10 Trends sowie den zukünftigen Rollen und Berufen.
Interview Mai 2018
Interview with Dr. Ulrich Kampffmeyer, Managing Director of PROJECT CONSULT Unternehmensberatung GmbH, Hamburg, Germany and a renowned expert on digital transformations, business intelligence and enterprise content management. Curriculum Vitae on Wikipedia https://de.wikipedia.org/wiki/Ulrich_Kampffmeyer; company website www.PROJECT-CONSULT.de. email: Ulrich.Kampffmeyer@PROJECT-CONSULT.com
Moscatel: Ulrich, you write and teach extensively about the cultural and social changes in work environments that are a direct result of the emergence of digital systems. Now that data is at the fingertips of everyone, what changes, positive or negative, should society expect to face that the business world may have already experienced?
Dr. Kampffmeyer: The business world is just at the start of the digital transformation; the information society is just a dense fog. The pace of digital transformation is accelerating day-by-day. In particular, the cloud, artificial intelligence, IoT and other current developments are driving so fast that there is a danger that they can get out of control. The more capable AI gets, the greater the danger that it becomes uncontrollable. Remember Shoshana Zuboff’s laws from 1988, that whatever software can be used to control, to manipulate, will be used for this purpose. And our society is currently not prepared for this change. Just look at the GDPR discussions. Data protection as a general necessity, data safety as the requirement for continuity, data privacy by default, information governance to keep control, maintain value, keep information accessible – These are basic requirements that should not be ignored like in the past. Future historians will call our era the dark age of the early information society.
Moscatel: You spent quite a bit of time at the Fraunhofer Institute developing imaging systems and processes to support archaeological studies. Given that images provide so much of the fuel for artificial intelligence, do you envision some of our older legacy systems and indexes ever providing value to future AI efforts?
Dr. Kampffmeyer: In the mid 80s I worked on pattern recognition, image processing, database systems and expert systems for archaeologists and prehistorians. Too early. Today taking a computer, drones and sensor systems to an excavation is standard. In those days …. But in regard to recognition, automated classification, expert systems and artificial intelligence the approach was similar to what is happening now 30 years later. The capabilities of software, hardware and self-learning algorithms are many times more sophisticated than in those days. But let’s take a look at so-called old-fashioned methods of organizing information. You mentioned “legacy” and “indexes.” Metadata are not legacy. It is a question of quality, control and governance. Controlled metadata, vocabularies and taxonomies are of special value to bigdata analytics, artificial intelligence and machine learning. The controlled datasets act as guides to train new technologies with high quality information and structures. This is important for automated indexing when capturing information, sharpening enterprise search for qualified results, and managing repositories in regard to compliance requirements. Especially when it comes to compliance, straightforwardly organized high-quality information is an asset. But AI will change the game here as well in the near future. Currently classification schemes and file plans are developed manually by academic rules. In the future software will analyze all information and organize itself by protection guidelines, user models, processes, value, retention etc. Digital transformation without information management does not work. Only those who know their information, manage it in a systematic way, systematically open it up, protect it consistently and use it efficiently can venture into digital transformation.
Moscatel: This series of interviews with global leaders in information management, risk and compliance seeks to find common values and themes in these disciplines across disparate cultures. I know that you are major advocate of standardization. Are there one or two common threads that run between all of the projects and people you’ve worked with that you also believe should be universally acknowledged?
Dr. Kampffmeyer: Standardization is a necessity. Everywhere. We do it with language, words, and grammar to enable understanding. We do it with hardware so that it supports interfaces and operating systems. We do it with software so that it can interact with other software and systems. We do this with the retention rules for documents in our records management systems. Standardization is everywhere – that is not the question. The real question is, what has to be standardized for which purpose? And is standardization something that inhibits innovation? And is standardization in streamlining and control in opposition to the culture of a group of people or an organization? The larger and more distributed an organization is, the harder it is to implement change and change culture. Old behaviour, language barriers, time zones, cultural differences etc. make common values hard to define. Processes to maintain values and make businesses run smoothly also need a kind of standardization. In my opinion, the cultural and organizational challenges of digital transformation are more important than technology and functionality. A common thread could be our old rule for information management projects: “strategy first, people, organization and processes second, technology last.” The risk of failure in this change process is not about new technology but about its adoption. Technology is still a facilitator for businesse, although this might change in the future with artificial intelligence. Less work for humans also means that human-driven use models and respect for human work will decline. This is a major challenge, because people often define their status by their work. So, this is a common thread in all projects, redefining processes while keeping workers involved, trying to overcome their fears of losing their jobs, and implanting a new mindset for a new type of work environment. With AI looming ahead, we even have to define what work is. Man is no longer the scale, the ruler, the canon.
Moscatel: Historically, Germany has led the way in record-keeping, from the Gutenberg printing press onward. What role, if any, do you think Enterprise Content Management has played in the present day, to drive business intelligence insights and knowledge management?
Dr. Kampffmeyer: Yes, Germans were supposedly always good at organization and keeping order – but in fact that’s a myth. In Germany the term Records Management is not known to many people. It is common only in regulated industries that use English terminology. German academics talk about the management of folders or documents (“Schriftgutverwaltung,” “Aktenverwaltung,” “revisionssichere Archivierung” … to name some typical German terms). Too few people are familiar with the correct term “record” as used by and the concepts behind “records management.” So, in fact, Germany is not very good at the records management seen in Anglo/American compliance culture. We use different terminology and different strategies in managing information. For example, there is no eDiscovery established in German GRC. The term ECM, Enterprise Content Management, was picked up late in Germany, in 2006. It is still not a common term, especially not with SMEs. We still use terms like “Dokumentenmanagement,” which is used differently from “document management” in the rest of the world. While internationally new terms like intelligent information management, content services or enterprise information management are coming into use, the German software industry still sticks to ECM and German terms (by the way, it might be a good idea to use the acronym ECM now for Enterprise CHANGE Management, because this is the important challenge for Digital Transformation). What we see in Germany is a revival of the term “knowledge management,” as supported by ISO 9001:2015 requiring “Wissensmanagement.” Information management software like an ECMS plays a major role in getting control of information and processes. Classic business intelligence is more and more being absorbed by bigdata analytics and artificial intelligence. A new generation of analytic tools encompassing BI methodology is on the way. ECM has played only a minor role, because knowledge management and BI have never been mainstream components in standard ECMS but only additions to the ECM portfolio from other software industries. The adaptation process, where ECM had to adapt to the cloud, mobile, analytics, social, automation, AI and so forth, led to the current crisis in the industry where new terms and visions are coming into use like IIM Intelligent Information management and content services platforms. In Germany the ECM software industry is stumbling, unsure which direction to go and no longer with a homogenous appearance in the marketplace.
Moscatel: Being at the forefront of Enterprise Content Management and systems design, you must have learned many lessons about development. And we live in a far more regulated environment then existed 30 years ago. Our challenges today intersect with privacy and security. What are the types of risks and concerns you believe developers of content management systems should be thinking about when building the next Documentum, SharePoint, Alfresco or Relativity?
Dr. Kampffmeyer: There is no future for the old dinosaur architectures of the big enterprise solutions like documentum. That’s why vendors and analysts have started discussing this content services thing. By the way, they forget that services have always been a basic concept of ECM – since the year 2000. The requirements of regulated industries and processes keep the traditional concepts of records management and archiving alive. But a general change is that there is no longer a difference between structured and unstructured information. A lot of ECM vendors unfortunately focused on this old paradigm and cared only about documents and unstructured content. Modern software – whatever you want to call it – has to cater to every type and technical format of information. The basic strategy for products is automation. Not only to eliminate human work and speed things up, but also to improve quality and establish new areas of business. Integration is still a major issue. We are no longer talking about traditional records management systems for records managers but about the integration of ECM functionality into other software. Interfacing is crucial. And like in the world of mobile apps, we will see services come up which automatically configure and integrate into other environments. Complex systems will be only manageable by AI-based administration software. So not just end-user relevant processes will be transformed, but also the configuration, administration and management of these solutions. And the services concept will make sure that ECM functionality is available in the same way as SaaS, PaaS, and on-premise. Another major change will be that end-users no longer see an ECM client because the functionality is integrated into the standard desktop environment. ECM will lose visibility on the desktop and becomes a standard infrastructure. All these developments will change the paradigm of the traditional ECM software architecture and functionality and require new development tools, listening to the user, faster testing and rollout, easier configuration, pre-configured business solutions, and easy to use end-user interfaces. A big challenge for all companies developing ECM software.
Moscatel: There’s been a lot of noise around GDRP, specifically the “right to be forgotten” and strict privacy and data retention safeguards, but we haven’t seen much intellectual discussion around the greater social benefits the law is intended to support. How do you see this “return to privacy” improving society when it seems that a lot of the younger generation not only dismiss the concept of privacy, but as Simon Sinek has noted, see themselves through the lens of the over-sharing Social Media community?
Dr. Kampffmeyer: GDPR has been in place for 2 years and is now only being enforced. May 25th saw a lot of panic reactions, although we learned “Don’t Panic” (May 25th is also Towel Day in memory of Douglas Adams … and GDPR is not 42!). It is not a return to privacy. Privacy requirements and regulations always have been here. But nobody really cared. We were careless with information and information sharing. And now we are complaining that the big internet giants use our data. The new quality of GDPR is twofold: For one thing, it is for all of Europe, and organizations dealing with European personal data and doing business in Europe also have to address it. So GDPR is becoming a de-facto worldwide standard. For another, it imposes severe fines for infringement of GDPR. This is a tool for enforcement we lacked in the past and that’s why everybody – late in the day – started to care about GDPR. But there is another side of the coin – small businesses, associations, photographers, and others also come under threat from GDPR. Where big companies hire more lawyers and establish a data protection regiment, small business are overwhelmed by bureaucracy. Information management software is a necessary tool for larger companies to manage all data as defined by GDPR. They need a map of what information of which quality, value and legal character is stored and processed where. Smaller business struggle with these requirements due to their size, larger business due to the complexity and the sheer amount of data involved. The social communities have a different view of GDPR requirements. On the one hand they have to pay more attention privacy, they must be able to deliver reports on where they store data and what they do with it. On the other hand, GDPR strengthens the big guys because small forums, blogs, communities, groups and business give up and move their communities to Facebook, Google+, LinkedIn, XING or somewhere else.
Communities like Facebook even used the necessary declaration of agreement to implement new technology like face recognition which interferes directly with privacy. Privacy by design, privacy by default will be major concepts of the future information society. But in reality, people choose the lazy options and don’t invest serious effort into the future information society. We leave this to science fiction authors and films, the CEOs of internet companies, and to populistic politicians. Privacy is not just about rights but also about obligations. These obligations don’t just entangle companies and public administrations. They apply to all of us, you and me. Everybody needs to take care of their own data and to respect the data privacy of all others. We cannot claim any right to be forgotten when we actively upload our directory of addresses to a social platform. In my opinion, data privacy and privacy rights are primarily a matter of education, which needs to start even before school. It is a task for developing a mindset about the value and the risks of information. Data privacy has to start in our heads.
Moscatel: Predictive coding was introduced almost two decades ago, and while the technology has advanced greatly, cost and complexity are still barriers to adoption. Will advances in artificial intelligence and machine learning help make these tools more affordable and accessible to smaller firms?
Dr. Kampffmeyer: First of all – we recently crossed a magic threshold in artificial intelligence. AI is now not only self-learning and self-optimizing, but like in evolution, it is self-replicating and self-expanding. An example is the Quine neural network. AI software is programming AI software and AI software is managing AI environments controlled by AI administration tools – machine learning will be a standard in this new virtual world. This AI is different from our perception of “intelligent.” It goes its own ways, inventing different methods, becoming more and more opaque to human perception and intellect. It is there, waiting around the corner. We are seeing a big war fought by Amazon, Apple, Microsoft, Google, IBM and many others for leadership in artificial intelligence. Today artificial intelligence is even free for end-users or comes with consumer products like all the SiriCoLexas. The longer it learns the more sophisticated it will become. And artificial intelligence will become part of every piece of software. The future of IOT with billions of devices will be only manageable by AI. So it is a matter of course that AI will become part of information management software, it will be part of every cloud offering, and it will reach smaller firms as well. The only delaying factor is legacy software, legacy management, legacy behaviour, legacy business models. Everybody will have to deploy AI, analytics, etc. to remain competitive. The overlapping, entailing, feedback-looping, accelerating innovation processes will encompass everybody. This is why I mentioned earlier that our old ideas of the information society with well-informed citizens having control of information and machines will be overturned by dystopian models of the science fiction world. Predictive analytics with artificial intelligence will play a major role in our fight to keep control, because software and systems will anticipate what we do, better and better. Entire industries will change. First those dealing with information only, like banks or insurance. Then manufacturing and farming will follow. Crafts might be able to resist the attack of the 3D printer. Thousands of other examples are discussed on the internet, in congresses and publications. Everybody talks about the digital transformation, how far we have come with it. I believe we need to talk now about what happens when everything is digitized.
Moscatel: Based on your many years of experience as a practitioner, lecturer and consultant, what sage advice can you offer to a young person just entering the field of information management and information technology?
Dr. Kampffmeyer: Well, education on information management is lagging behind the technology and information revolution. Learn to think for yourself, learn languages, learn how to communicate. Learn methodologies, learn philosophy, learn to adapt to change, learn to not stop learning throughout your life, learn to find meaning in a life with no meaningful work for humans. Education and training in universities is good but it is academic and follows old paradigms. Vendors mostly educate new staff on their own, which leads to their staff thinking only in terms of their product. End-user organizations train with a focus on their business model, so that new ideas have to fight for some time for acceptance. Don’t become a librarian – that job will be taken by AI. Don’t become a programmer – that job will be taken by AI. Go for information architecture, information communication, or probably the best advice is to study something which is of real interest to you, what you really love, which gives you intellectual satisfaction – and then move into information management as a job. I studied archaeology, prehistory, art history, Near Eastern studies, information science, and soil science. This combination gives me a good feeling about the value of information, long-term preservation and access to information, organizing, ordering and classification of information, detective work from information fragments to create the whole image, the importance of culture, scientific methodology, strategic thinking and other things you need to be an information management consultant.
Interview Dezember 2022
Moscatel: How did Covid change working behaviour and what was the impact on remote work?
Dr. Kampffmeyer: The COVID-19 pandemic had a significant impact on the way that work is organized and performed. Covid gave collaboration and home work a big push. Remote work became the standard procedure, as many organizations implemented measures to encourage or require their employees to work from home in order to reduce the spread of the virus. This shift to remote work had a number of implications for work habits and behaviors: Increase in the use collaboration tools, video conferencing, online project management software, cloud-based communication software a.s.o.. A big challenge was to adapt „old school“ software to safe and secure use from remote workstations outside the organization. The shift to remote work with more flexible work schedules, less personal communication with colleagues and new responsibilities gave pressure on work-life balance working from home. Many have struggled to adapt to the new way of working, particularly if they were not used to working remotely or if they did not have a dedicated workspace at home. Others have found it difficult to maintain work-life balance or to stay motivated and productive without the structure and social support provided by a traditional office environment. In regard to the organizations and IT departments the pandemic had a huge impact how they approach work and productivity for “white collar” workers as well staff still working onsite. On one hand this included a greater emphasis on trust and autonomy for employees, on the other hand more stringent communication, collaboration and control in order to stay connected and productive. Companies had a lot to do in short time, like implementing virtual private networks (VPNs) or remote desktop software, as well as training employees on best practices for working securely. In terms of safety, organizations needed to ensure that employees are able to work in a safe and healthy environment, whether that is in an office with Covid protection measures or at home. Now, after Covid, companies need to clean up all this ad-hoc measures and consolidate software and repositories.
Moscatel: What is the impact on the future of Information Management?
Dr. Kampffmeyer: I envision 10 Trends for Information Management in the coming years. First there is increased use of artificial intelligence (AI) and machine learning: AI and machine learning technologies are likely to become more prevalent in information management, enabling organizations to automate and improve various processes, such as data analysis, classification, and organization. Data Privacy and data security come second: the amount of data being generated and stored continues to grow exponentially. So IT departments and organizations need to prioritize the security and privacy of this data to protect against potential breaches and cyberattacks. Third is Cloud-based solutions, as private IaaS or PaaS, as well as public SaaS. These solutions offer adopt cloud-based solutions for storing, organizing, and analyzing data, as these solutions offer scalability, flexibility, and cost-effectiveness. Trend number four is the integration of systems, solutions, data and repositories in an heterogenous environment. Departmental or solutions silos are “out”. Five – Increased focus on data and information governance including policies, procedures and software implemented rules for the management, control and use of information. This includes as well a focus on ethics. Number six is big data and analytics to better organize, evaluate, automate, and use data, information and digital knowledge. My point number seven is more focus on visualization. New user interfaces which fit the different devices from onsite PCs, remote PCs, notebooks, tablets and mobile phones – all with probably different operating systems. Eight goes with number seven: Data & Information literacy. Data and information become more important in regard to automation, decision making and workflow control, so users have to be educated to make us of the new solutions. My ninth trend is the advancing use of chatbots and virtual assistant like GPT-3 with huge language models and in depth training repositories. These solutions change processes and the interaction between software and humans. But the benefits outweigh the risks and current fears of employees. Last not least, trend number 10, “democratization” of information. Users get more access, more overview, more functionality and more responsibilities. This helps to improve processes especially in regard to customer services. The employee is no longer restricted to an island of information but gets a 3600 view to all related, interconnected information in context.
Moscatel: What about new roles and professions in information management & information governance?
Dr. Kampffmeyer: Automation, Chatbots, the use of analytics and artificial intelligence, machine learning and other advanced technologies will “kill” a lot of jobs in the offices and back-offices. But there will be a lot of new roles and highly qualified professions.
We need data and information governance specialists, who are responsible for developing and implementing policies and procedures for the management and use of data within an organization including defining data standards, establishing protocols for data access and security, and ensuring compliance with relevant laws and regulations.
Data scientists who are skilled in the analysis and interpretation of large sets of data. They are responsible for extracting insights and insights from data, and for developing algorithms and models to inform decision-making.
There will be data and AI artificial intelligences ethicists. They are responsible for advising organizations on ethical issues related to the use and management of data, such as privacy, consent, and bias. They help developing and implementing policies and procedures to ensure that data is used ethically and responsibly. The role of an AI ethics officer would be to ensure that AI systems are designed and used ethically and in accordance with relevant laws and regulations.
With respect to laws and regulations there is a need for specialized information governance lawyers. These lawyers need to know all laws, regulations, verdicts and legal developments related to the management and use of information, and their implementation in the organization. They check and advise on compliance issues and help to develop policies and procedures to ensure compliance with relevant laws and regulations.
There is a huge need for data security specialists, who are responsible to develop, implement, protect and control information. This includes establishing protocols for data access and security, implementing security technologies, and training employees on best practices for security.
A new profession is the machine language (ML) engineer. He designs implements, controls and improvs the models, algorithms and training materials. He is as engaged in the integration of these technologies in other software environments.
An analytics consultant is useful to help the company, management and employees to understand and make sense of their information, providing insights and recommendations for decision-making and strategic planning. This includes surveys and collection of user requirements for improvement of software and processes.
A data visualization specialist may help to develop useful user interfaces to improve efficiency and effectiveness of the use of information. He may closely work together with a process automation specialist.
The process automation specialists role focusses on designing and implementing automated processes and workflows, including the use of BPM Business Process Management, RPA Robotic Process Automation, Artificial Intelligence, Analytics and ML Machine Learning. The goal is to streamline and optimize business operations.
All of this combined establishes the need for change management specialists. They are responsible for helping organizations to effectively plan and execute changes related to the adoption of new technologies, new processes and “new work”. They make sure that the organizations reaches the set goals and improvements with integrating all people of the company, their skills and their potentials.
There might be even more new jobs i.E. capturing information with scanning, checking the accuracy and quality of automated generated results, enhanced helpdesk with creation of video courses to support home workers, interface specialists, who manage and monitor the interconnection of different systems: on premises, in the cloud, or hybrid.
And there are new roles and positions on the “C”-level – Chief Ethics Officer, Chief Information Officer, Chief Security Officer, Chief Compliance Officer, and more.
There will develop a lot of roles in the future we cannot even envision today.
2 Kommentare zu “Emerging from the Dense, Digital Fog II”
Artificial Intelligence: Emerging from the Dense Digital Fog - Version 2.1
Inzwischen hat mir Rafael Moscatel seinen narrativ gestalteten Textentwurf für die zweite Auflage des Buches „Tomorrow’s Jobs Today“ bereitgestellt. Anstelle des reinen Interview-Textes vom Dezember 2022 (siehe oben) soll das Buch nun einen eher erzählerischen Charakter bekommen. Die Antworten 2 und 3 aus dem Interview wurden in dem folgenden Text, der bei Rafael unter der URL http://bit.ly/3mB41Ld abgerufen werden kann, zusammengefasst.
——— Entwurf 09.02.2023 ———-
Artificial Intelligence: Emerging from the Dense Digital Fog
Rafael Moscatel; Artificial Intelligence, Professional Development
The following excerpt is based on the book Tomorrow’s Jobs Today, available at fine booksellers.
Futurist Roy Amara says, “We tend to overestimate the effect of a technology in the short run and underestimate the effect in the long run.” This book offers a solid perspective on where we are today with Artificial Intelligence, Big Data, Blockchain, Privacy, and the Internet of Things, as well as a near-magical crystal ball into what tomorrow holds. In our new book, Tomorrow’s Jobs Today, we spoke with thought leader Dr. Ulrich Kampffmeyer about what this future means for us all.
Dr. Ulrich Kampffmeyer was an early pioneer in enterprise content management who pivoted to machine learning and AI. He holds a master’s in archaeology, a master in information technology, a diploma in natural sciences for archaeology and information science, and completed his Ph.D. in prehistory at the University of Göttingen. He’s the Managing Director of PROJECT CONSULT and a renowned digital transformation, information management, information governance, and business intelligence expert.
Dr. Kampffmeyer firmly believes that with AI looming ahead, we will have to redefine what work is. “Man is no longer the scale, the ruler, or the canon,” he explains. It’s a subject he’s passionate about, and he’s written and taught extensivelyon cultural and social changes observed in work environments that are a direct result of the emergence of these digital transformations. Now that data and AI are at everyone’s fingertips, he thinks there is a real danger that technologies like AI will get out of control and perhaps already have to some degree.
He says society has already crossed the magic border of AI, which is now not only self-learning and self-optimizing but self-replicating and self-expanding. One example is the Neural Network Quine.5 AI software is now programming AI software, and AI software manages AI environments controlled by AI administration tools. So machine learning skills will be standard in this new virtual world. And this AI is different from our traditional perception of intelligence. It goes its own ways, inventing different methods and becoming transparent to human perception and intellect. “It is here, not just waiting around the corner,” Dr. Kampffmeyer explains. “We see a big war being fought by Amazon, Apple, Microsoft, Google, IBM, and others for that pole position.” That also means they’re looking for talent in AI and willing to pay top salaries.
The doctor’s perspectives on AI follow from those of Shoshana Zuboff, one of the first tenured women at Harvard Business School, who predicted in the early 80ies:
And to Dr. Kampffmeyer, neither our business communities nor our societies are currently prepared for the changes ahead, which is why getting people involved in shaping the tools from not just a technical or administrative but an ethical standpoint is so critical to him. He points to initiatives like the General Data Protection Regulation in the EU as necessary, where a requirement for continuity defines data safety, data privacy is the default, and information governance is used to maintain control. In Europe, dozens of initiatives to prepare the European Union for the Digital Age are underway, including many new directives pertaining to ethical artificial intelligence. However, he feels these are basic requirements that until recently have gone ignored, and future historians may view our era as a sort of dark age of the early information society.
He spent years researching at the Fraunhofer Institute, developing imaging systems, digital optical archiving solutions, and expert system processes to support archaeological studies. And because images, especially when transformed into structured data, have provided much of the fuel for artificial intelligence engines to learn from, we asked him if he envisioned some of our older legacy systems and indexes providing value to future AI efforts. That’s a question many job seekers are asking themselves today, and fortuitously, they’re finding that their prior experience and skill sets developed with earlier technologies do indeed aid them in transitioning to an AI practitioner.
Dr. Kampffmeyer says his work on pattern recognition, image processing, database systems, and expert systems for archaeologists and prehistorians prepared him for some of what he deals with today. And today, he says, “taking a computer, drones, and sensor systems to an excavation site is standard, with capabilities of the software, hardware, and self-learning algorithms far more sophisticated than in those days.” But while yesterday’s content is less and less important to today’s AI, he does think job-seekers need to consider the value of earlier methods of organizing information. Metadata is one example. That discipline is not a legacy we have entirely left behind. It’s still a requirement for quality, control, and governance that fuels AI today. And it’s a skill you can carry forward and apply to almost any career examined in this guidebook.
Later in his career, he designed products for document management vendors before working as an advisor in information management strategy. Records Management requirements pertaining to controlled metadata, vocabularies, and taxonomies are of special value to big data analytics, artificial intelligence, and machine learning today. Controlled data sets work as guide poles to train new technologies with high-quality information. This is useful for automated indexing when capturing information, sharpening enterprise searches for qualified results, and managing repositories with compliance requirements.
Especially when it comes to governance and compliance, organized, high-quality information is a valuable asset. It can be used for training AI properly. But AI will change the game as well in the near future. Currently, classification schemes and file plans are developed manually by academic rules. In the future, Dr. Kampffmeyer points out that software will analyze all our information and organize itself by protection guidelines, user models, processes, value, and retention. For example, he says, “The automatic generation of virtual folders with easy access and intuitive presentation of information is the goal.”
Another window of opportunity for career seekers that Dr. Kampffmeyer sees, often related to metadata management and structuring information, is in the work around standardization, which applies to the AI discipline and technology jobs across the board. He believes standardization is a necessity. Everywhere. We standardize our language, terms, and grammar to enable understanding. We do it with hardware so that it supports interfaces and operating systems. We do it with software so that it can interact with other software and systems. We do it with document retention rules in our records management systems. Standardization is everywhere; that’s no question. But a question for tomorrow’s workers is what has to be standardized and for which purpose?
AI also involves change management, another area where workers are desperately needed. And the larger and more distributed an organization becomes, the harder the job of implementing change and changing culture. Old behavior, language barriers, time zones, and cultural differences can sometimes make common values and standards hard to define, says Kampffmeyer. Creating or refining business processes to keep proven values and make businesses run smoother is a kind of standardization.
But this, too, might change in the future with artificial intelligence. And less work for humans means that human-driven models and respect for the dignity of human work will decrease. That’s a major social challenge because people often define their status through their work. “Who will build and redefine our new work processes, keep workers involved, try to help them overcome their fears of losing their jobs, and be responsible for implanting a new mindset for a new type of work environment?” posits Dr. Kampffmeyer.
Today, AI is even free for end-users or comes with consumer products. He says the longer it learns, the more sophisticated it will become. And AI is quickly becoming part of every piece of software. The future of IoT, with billions of devices, will only be manageable by AI. It will become part of every cloud offering and will reach smaller firms. The delay factors are legacy software, management, behavior, and business models.
Dr. Kampffmeyer believes strongly that in terms of technology, there is no bright future for old dinosaur architectures and big enterprise solutions. Modern solutions must care for every type of technical format and information available. The basic strategy for products must be automation. Not only to get rid of human work and to speed it up but to improve quality control and establish new areas of business opportunity. Modular cloud solutions providing business solutions supported by AI will become the standard, but the dependence on the correctness and availability of information is also growing,” Kampffmeyer says.
Integration is still a major issue, though. For example, some organizations are no longer talking about funding traditional records management systems for records managers but driving the integration of that functionality into other software. Interfacing and application programming interfaces (APIs) are now the norm. And like the world of mobile apps, we will see services that integrate and configure automatically into other environments. However, all of these advancements and changes require people’s talents to develop and support them.
Complex systems in the future might only be manageable by AI-based administration software. So not only will end-user relevant processes be transformed, but also the configuration, administration, and management of these solutions. We will lose a lot of traditional office and It-management jobs with automation. On the other hand, these new technologies create new job descriptions, roles, responsibilities, and skill requirements.
The IT services concept will likely ensure that traditional functionality is available in the same way as Software-as-a-Service, Platform-as-a-Service, and on-premise solutions have. Old systems will probably lose visibility on the desktop and become standard infrastructure. All of these developments will change the paradigm of traditional software architecture and functionality. And Dr. Kampffmeyer emphasizes they’ll require new dev-ops, new development tools, listening to the user, faster testing and roll-out, easier configuration, pre-configured business solutions, and easy-to-use end-user interfaces.
The overlapping, entailing, reverse-causing, accelerating innovation processes AI produces will encompass everybody, whether we like it or not. That’s why Dr. Kampffmeyer believes our ideal of an information-driven society with well-informed citizens controlling that information and its machines could be overturned by dystopian models of a science fiction nature. So, if you’re worried about that and love AI, maybe you should throw your hat in the ring! Yes, automation, chatbots, the use of analytics and artificial intelligence, machine learning, and other advanced technologies will “kill” many jobs in the offices and back offices. But there will be a lot of new roles, and highly qualified professionals will be born.
The doctor’s advice for new graduates and people trying to get into the business is straightforward but deserves repeating. “Learn to think for yourself, learn languages, learn how to communicate, learn methodologies, learn philosophy, learn to adopt change, and learn not to stop learning throughout your life!” he says encouragingly. “And prepare for the future with more automation, more use of Artificial Intelligence, and more information governance and security challenges – even in the learning and training environments you will use. Lifelong learning, supported by e-learning software and using large knowledge bases with novel interfaces for information delivery, is the key to success in new technology-driven subjects.”
What kinds of AI-related jobs are out there?
Tomorrow's Jobs Today - 2. Auflage
Die zweite Auflage – in verändertem Stil – des Buches von Abby und Rafael Moscatel ist im März 2023 erschienen: Amazon.com: Tomorrow’s Jobs Today: Wisdom & Career Advice from Thought Leaders in AI, Big Data, Blockchain, the Internet of Things, Privacy, and More: 9798987906125: Moscatel, Rafael, Moscatel, Abby. Das Buch basiert auf Interviews mit verschiedenen Persönlichkeiten der IT-, Information-Management- und Information-Governance-Branche. Dr. Ulrich Kampffmeyer ist prominent in der Publikation berücksichtigt. Die erste Auflage – mit den originären Interviews – wurde vom Markt genommen.
Abby und Rafael Moscatel schreiben zur Publikation:
„ … this second edition is markedly different from the prior in several ways: