Navigating the twilight zone - pathways towards digital transformation of food systems
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The document discusses navigating the "Twilight Zone" of digital transformation in food systems. It outlines the need for a paradigm shift from standalone applications to integrated systems involving multiple stakeholders. It proposes looking through 5 lenses: business models in the data economy, responsible data sharing, digital inclusiveness, integrative artificial intelligence, and cross-sectoral integration. An integrated approach is suggested involving stakeholders from design to evaluation, with alignment of public and private funding to support digital innovation projects in the Twilight Zone.
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Navigating the twilight zone - pathways towards digital transformation of food systems
- 1. Navigating the Twilight Zone Pathways towards digital transformation of food systems Mansholt Lecture 2021 Sjaak Wolfert, Brussels, 22 Sep. 2021
- 2. Outline of this lecture 2 1. Entering the Twilight Zone of digital transformation 2. The need for a paradigm shift 3. 5 lenses to look through when navigating the Twilight Zone 4. An integrated approach for navigating the Twilight Zone 5. Recommendations & conclusions
- 3. Twilight Zone System of systems Stand-alone application IT Integration level Number of stakeholders Process operator Business ecosystem App Farm information system Chain information system Data Platforms Production process Farm management Food supply chain Food Data Economy Data Spaces Food systems Need for Paradigm Shift The evolution of IT in agri-food
- 4. The need for a paradigm shift 4 • Beyond user-centred design • Focus on data sharing between multiple stakeholders in various roles • (Eco)System of (eco)systems: • Multi-sided business models • Complex technical integration • Funding also becomes complex
- 5. twilight zone Utilizing public-private capital in Twilight Zone public innovation support private innovation capital potential innovation capital
- 6. 5 lenses to look through navigating the Twilight Zone in a responsible, successful way 6 1. Business models in the data economy 2. Responsible data sharing 3. Digital inclusiveness 4. Integrative artificial intelligence 5. Cross-sectoral integration
- 7. Business models in the data economy 7 • Multiple economies of digitalisation • New values of data: • Governance challenged at various levels: corporate, network, platform, ecosystem records intelligence governance currencies
- 8. • Willingness to share data is key for digital innovations • Make data sharing responsible: • Co-creation with stakeholders of data-sharing values and practices Responsible Data Sharing 8 fair data markets control care for commons trust
- 9. • Critical consideration when designing digital solutions, technological/organizational infrastructure • Development of skills and expertise of existing and new stakeholders • Exclusion: Inclusion: • Include explicitly in design! Digital inclusiveness 9 deliberate? beneficial? unvoluntary? harmful?
- 10. Integrative Artificial Intelligence 10 • Data-intensive discoveries are enabled by new collaborations beyond disciplinary boundaries • Combine: • Transparent and explainable, well-founded on (existing) food systems knowledge novel sensing technologies big data infrastructures machine learning artificial intelligence
- 11. • Integrated approach to rural development cross-sectoral services and platforms • Share and re-use knowledge and technology between sectors • Active involvement of food systems in cross-sectoral standardization • Opportunities for circular economies & citizen dialogues • Connection with advanced IT ecosystem is key for food systems Cross-sectoral integration 11
- 12. Use Case project Business Modelling, Governance & Ethics LARGE SCALE MVP2 MVP1 MVP.. Data Science & AI Ecosystem Development 2. Implementation & Integration 3. Testing & Demonstration 4. Evaluation 1. Design An approach for navigating the Twilight Zone
- 13. Connecting the Dots – Digital Innovation Hubs 13 DIH: local one-stop shop in the proximity of stakeholders Service provision: technology, business and ecosystem development supported by Competence Centers Network of DIHs and Competence Centres: • share and re-use knowledge, also cross-sectoral! • continuous project alignment by matching public and private funding
- 14. Digital innovation projects in the Twilight Zone need: • an integrated approach with constant interaction between all relevant stakeholders supported by multiple disciplines • structural ecosystem development facilitated by aligning public and private funding instruments Recommendations 14
- 15. • Digitalization towards a new Data Economy for Food Systems has entered a Twilight Zone • Navigating requires looking through various lenses • An interactive, multi-disciplinary, integrated approach is essential • Fragmentation must be overcome by continuous alignment of public and private funding Conclusions 15
- 16. Thank you for your attention! Sjaak Wolfert sjaak.wolfert@wur.nl Co-authors Lan van Wassenaer, Simone van der Burg, Mark Ryan, Laurens Klerkx, Kelly Rijswijk, Mariette McCampbell, Ioannis Athanasiadis, George Beers 16 See you in the bright future of the new Data Economy for Food Systems!
Editor's Notes
- Welcome to the Twilight Zone of the digital transformation of food systems! I am very excited about the opportunities digitalization has to offer food systems. I can see the light of the new data economy for food systems dawning. However, I think that we are currently still in the darkness of this development and when stepping towards the light we should be careful where to put our feet and we do not stumble. Because in other domains, that are ahead of the food system, we have seen already several pitfalls. Think about the Cambridge Analytica case in which data of millions of Facebook users was misused for political advertising. Or cases of ethnic profiling by AI algorithms. And what about food delivery services that are locked-in to the system of big giants such as Takeaway.com? Shouldn’t we expect similar developments within the food system or isn’t it already happening in this last example? The objective of my lecture is therefore to show how to navigate through this Twilight Zone of digital transformation of food systems in a responsible way. Are you ready to follow me on this journey?
- The outline of my lecture is as follows: Entering the Twilight Zone of digital transformation The need for a paradigm shift 5 lenses to look through when navigating the Twilight Zone An integrated approach for navigating the Twilight Zone Recommendations & conclusions
- When analysing the evolution of IT in agri-food, we can distinguish two axes along which this is taking place: [CLICK] the IT integration level on the x-axis: ranging from stand-alone application to the system of systems level situation in which many systems have to work together seamlessly [CLICK] at the y-axis the number of stakeholders involved: ranging from a single process operator to complex business ecosystems in which many actors are interacting with each other When [CLICK] combining these two axes we can distinguish: [CLICK] Single production processes targeted by single apps [CLICK] Farm management supported by farm information systems [CLICK] Food supply chains supported by chain information systems [CLICK] Food systems of producers and consumers addressed by data platforms [CLICK] A new food data economy based on emerging data spaces Although the lower part of this ‘ladder’ is still relevant and needed, the [CLICK] Twilight Zone can be identified at the top. Nowadays we are talking a lot about food systems in which the first data platforms are emerging such as DjustConnect here in Belgium. But these are just in an early stage of development. We want to go to a Food Data Economy grounded in Data Spaces that are set as an important strategic goal by the European Commission. But it is still quite unclear how to get there. Now you can argue if this is just a continuous development or that this requires a paradigm [CLICK] shift?
- We think it does and let me explain what this paradigm shift is about. We need to go [CLICK] beyond user-centred design because in complex business ecosystems it is not always so clear anymore who are exactly the users of various systems and data. One time you are a user of data, but at the same time you can also be a producer. In the twilight zone the [CLICK] focus is not anymore on single systems to support processes or management, but on sharing data between multiple stakeholders in various roles. So looking at the intersection of both ends of the axes you could say that we have a situation of [CLICK] a system of systems – or ecosystem of ecosystems, where you can find multi-sided business models and also the technical integration becomes rather complex. Finally, [CLICK] funding also becomes more complex in the twilight zone. Let me explain that by the next slide.
- The question is how to utilize public-private capital in the twilight zone? If we look at the [CLICK] common innovation pathway from invention through prototyping and piloting to market introduction and expansion, it is logical how the [CLICK] public innovations support diminishes while the amount of [CLICK] private innovation capital is increasing. If you sum up the two you get the [CLICK] potential innovation capital that is available and you see that this is especially interesting in the middle. And this is exactly where the [CLICK] twilight zone is situated: concepts and prototypes are promising but the public support is diminishing while for most private investors it is still too risky, resulting in many promising innovations that will never see the light or at least market introduction is very slow. Financing instruments that are able to match and align both forms of capital are needed for breakthroughs. That will greatly support navigating through this twilight zone.
- To navigate through the twilight zone, we identify five lenses to look through if you want to do it in a responsible, successful way: [CLICK] Business models in the data economy [CLICK] Responsible data sharing [CLICK] Digital inclusiveness [CLICK] Integrative artificial intelligence [CLICK] Cross-sectoral integration Let’s have a closer look at these five lenses.
- When looking at business models for the data economy, we see [CLICK] multiple economies emerging as a result of digitalization. As shown in this figure, economies of scale, scope and speed are blended into a new generation of business models featured by digital platforms, ecosystem thinking and new types of currencies such as cryptocurrencies. Well-known examples of this development are Amazon and AliExpress. In the data economy we therefore see the [CLICK] new values of data ranging form being simple records to intelligence, currencies and ultimately governance. In the latter case you can think of AI algorithms or smart contracts that are taking over processes of traditional institutions such as banks, notaries and governments. So it is clear that data economy is not only driven by smart technologies, but it is [CLICK] challenging governance at various levels at the same time: at corporate, network, platform and ecosystem level!
- The second lens is about responsible data sharing. First of all, it is clear that the [CLICK] willingness to share data is key for digital innovations and to move towards the food data economy. However, amongst others, due to all kind of societal concerns, it becomes clear that this is not something that speaks for itself. Therefore we plead for [CLICK] making data sharing more responsible by an integrated approach for: Fair data markets. But what is fair? Our experience learns that this has to do with underlying morals and values. This means that there are no easy, straightforward answers, but it helps already to create transparent dialogues around this. Give people more control over their data by appropriate authentication mechanisms Create trust and Take care of the commons by framing data into the right contexts to prevent from misuse and abuse. This is of course easier said than done and there are many unresolved issues. But lessons learnt from projects such as IoF2020 indicate that [CLICK] co-creation with all relevant stakeholders of data-sharing values and practices helps.
- The third lens is about digital inclusiveness which is very much in line with the previous lens. Traditionally, well-known in- or exclusion factors include being female, disabled, illiterate, indigenous, or poor. In the twilight zone towards the data economy of a complex system of systems and business ecosystems these factors can be amplified and new factors emerge, such as access to or control over data. Therefore it remains [CLICK] critical to consider this when designing digital solutions, technological and organizational infrastructure. It is not only a simple matter of money to get access to technology or data, but [CLICK] development of skills and expertise of existing and new stakeholders could be more important. Finally, [CLICK] exclusion or inclusion can also be a choice. There might be cases where stakeholders would like to opt out because for example adopting new technologies also brings additional, unwanted responsibilities. So, unvoluntary inclusion is not always beneficial and could even be harmful. However, the choice of exclusion or inclusion is not always cut-and-clear, but can pop-up suddenly. Therefore it is important to [CLICK] account for this in the design of digital innovations.
- The fourth lens is about integrative artificial intelligence. Now everybody is talking about AI these days as the latest hype, but good examples of applications in food systems are still rare. Experiences from other domains - that are more ahead – learns that [CLICK] data-intensive discoveries are enabled by new collaborations beyond disciplinary boundaries. For example, the disciplines of machine visioning and phenotyping had to come together to generate successful applications of automated mapping of crop or animal traits. So it is important to [CLICK] combine disciplines or developments such as novel sensing technologies, artificial intelligence, machine learning and big data infrastructures. Success is also dependent on [CLICK] transparency and explainability of AI-algorithms, that is well-founded on (existing) food systems knowledge. Otherwise it won’t be accepted by users.
- The fifth and final lens is the one of cross-sectoral integration. In the economies of scale, scope and speed it can be very beneficial for the food system to jump on the train of existing developments within other sectors and [CLICK] develop cross-sectoral services and platforms. While most of the underlying digital technologies at stake are not unique for food systems it would be good to [CLICK] share and re-use knowledge and technology as much as possible. This requires for example active involvement of the food systems sector in [CLICK] cross-sectoral standardization. At the same time we believe that cross-sectoral integration also provides [CLICK] new opportunities for circular economies and citizen dialogues. In conclusion, it will be very beneficial if the food ecosystem gets well connected to the [CLICK] advanced IT ecosystem.
- Such an integrated approach targeting the challenging twilight zone of digital innovation was developed and applied within the Internet of Food and Farm 2020 (IoF2020) project. The heart of this approach is formed by [CLICK] use case projects in which you develop a certain digital solution. A use case means that you already start to use the solution in the project. It is tested in a real-life environment in which [CLICK] user involvement is a key success factor at four points of the development cycle: [CLICK] Design [CLICK] Implementation and integration [CLICK] Testing and demonstration [CLICK] Evaluation Dependent on the outcome of the last step you are going to adapt your design and go through these steps again. [CLICK] The spiral in this picture indicates how you go through the development cycle, but each time you try to end up at a next level. This next level is determined by so-called minimum viable products (MVPs). A minimum viable product is a version of a product, or service, with just enough features that can be evaluated by the users. Each next MVP adds more features until you reach the stage at which the digital solution is mature and can be introduced at a large scale. This means that a minimum viable product is more than a technical prototype to see if it works. Features should include all aspects of the five lenses that I have presented before. This is done by supporting use case projects by three groups of different scientific disciplines: [CLICK] Data science and AI [CLICK] Business Modelling, Governance and Ethics [CLICK] Ecosystem Development This approach was applied to 33 different use case projects from various sectors and as you can see the arrows in this picture as two-way arrows. This means that for various topics use case projects could share knowledge and learn from each other while a vast knowledge base was build up around e.g. responsible data sharing, data-driven business models or AI-applications. Also general knowledge gaps were identified.
- Currently, we are replicating this approach by connecting the dots all over Europe in projects such as SmartAgriHubs, agROBOfood and Digital Agri Hub. This is done by identifying [CLICK] Digital Innovation Hubs that act as local one-stops shops in the proximity of stakeholders, so very much working at a regional level. DIHs provide [CLICK] services concerning technology, business and ecosystem development supported by Competence Centers, aligned with the integrated approach that I just presented in the previous slide. In this way we try to develop a [CLICK] network of DIHs and Competence Centres that share and re-use knowledge - also cross-sectoral. Moreover, through open calls we try to attract additional private and public funding to create continuous development of innovations throughout the whole innovation lifecycle.
- In the booklet we have provided a long list of recommendations that I cannot present now, but if I try to highlight the most important ones, these would be: [CLICK] Digital innovation projects in the Twilight Zone need: [CLICK] an integrated approach with constant interaction between all relevant stakeholders supported by multiple disciplines looking through the five lenses I presented [CLICK] structural ecosystem development should be facilitated by aligning public and private funding instruments
- Coming to a conclusion. [CLICK] Digitalization towards a new Data Economy for Food Systems has entered a Twilight Zone where the light is dawning but developments are still in an early stage [CLICK] Navigating requires looking through various lenses of both technology and social sciences and humanities [CLICK] An interactive, multi-disciplinary, integrated approach is essential for navigating through the twilight zone in a responsible and robust manner. [CLICK] Fragmentation of innovation projects must be overcome by continuous alignment of public and private funding and creating a network of DIHs and CCs.
- And with that I want to thank you for your attention! And I would like to acknowledge my co-authors: Lan van Wassenaer, Simone van der Burg, Mark Ryan, Laurens Klerkx, Kelly Rijswijk, Mariette McCampbell, Ioannis Athanasiadis and George Beers. [CLICK] Hope to see you in the bright future of the new Data Economy for Food Systems!