Software Business

Connected products and DevOps allow for a fundamentally different way of working in R&D. Rather than focusing on efficiency of teams, often expressed in terms of flow and number of features per sprint, we are now able to focus on the effectiveness of R&D as expressed in the amount of value created per unit of R&D. We have developed several solutions, such as HYPEX, HoliDev and hierarchical value models, but companies still experience challenges. In this paper, we provide an overview of the trends driving the transition to focusing on effectiveness, discuss the challenges that companies experience as well as the requirements for a successful transformation.

Software startup research is an emerging field of study that corresponds to the significance of software startups in the modern economy. The evolution of the software startup research field is inspected in this paper through an examination of the scientific publications and contributing disciplines. The crucial role played by the Computer Science discipline in the development of software startup research is highlighted, as well as the interdisciplinary collaboration happening in the field. An insider’s view is also offered on the contribution that a purposeful research network made to grow software startup research.

Software intensive business research is rapidly evolving. Over the last decade we have witnessed a surge in research output but as the field matures, its future remains unsure. In this paper an overview is provided of the highlights and trends of software intensive business research. We briefly discuss the most cited papers in the domain and provide a hype cycle for software intensive business research. With this paper, we hope that researchers can forge more solid research strategies for themselves in the domain, to achieve longevity, academic depth, and impact.

Software development companies are venturing towards collaborative approach and software ecosystems (SECO) participation. Over the years, many papers have been written and different modelling languages were proposed to capture the interactions between the SECO participants. What is missing, however, is a comprehensive meta-model describing possible entities and relationships that constitute a SECO. The goal of this paper is to create a common language for academic researchers for software ecosystems by creating such a meta-model. We constructed the meta-model by extracting and grouping entities and relationships from research papers. The meta-model consists of 5 themes: actors and roles, products and platforms, boundaries, ecosystem health and strategy. We advocate that our meta-model allows for easy sharing and comparing of case studies and the generalization of results across studies. We present the results from initial expert evaluation of the meta-model.

Currently emerging Industrial Internet of Things (iIoT) platforms form open and flexible networks with the aim of facilitating the integration of various stakeholders in the generation of platform-based added value. The ecosystem emergence process is still underresearched and remains a challenge for the platform providers. In this short paper, we analyze the ecosystem development by Siemens for the platform MindSphere to understand its evolution, based on the sequence of entered partnerships, and their interplay with the established platform boundary resources (BR). Based on this case study, our research identifies insights about how Siemens developed its ecosystem during three distinctive phases. Our analysis demonstrates a roadmap, helping to understand how Siemens managed to integrate distinctive company types as partners in the MindSphere ecosystem. The findings add to the theory on platform emergence by embedding it into a complex Business-to-Business (B2B) context of iIoT.

Currently, software acquirers and suppliers as well as their relations have been investigated as a software ecosystem (SECO). In a SECO, an organization wants to achieve its business objectives supported by technologies based on a common ecosystem platform. Modifications on technologies can make essential systems unsupported or low performance. Thus, IT managers should consider information about technologies and their relationships. Such information may be spread in different documents and/or difficult to analyze due to the lack of support. As such, related attributes assist IT managers and architects in making decisions on the IT architecture modification, i.e., the set of technologies supporting products and services adopted by an organization. This research aims to identify architecture attributes that affect a SECO and its platform and technologies from the literature. With the intention of comparing this research to a well-accepted standard, ISO/IEC 25000 characteristics were analyzed against architecture attributes. Then, we have evaluated such attributes with experts from industry and academia based on a survey research. As a result, 64 attributes were identified and grouped by 11 critical factors. Critical factors are macro attributes that encompass other attributes. Then, a better understanding on how IT managers and architects’ choices can affect SECO could help them to take actions to mitigate negative effects.

Increasing competition forces companies to find new business opportunities by building business ecosystems together. The business ecosystem, where a set of companies develop and provide digital services together for a specific customer segment, can be referred to as a software ecosystem. The planning of ecosystems has been researched in some case studies, but more comprehensive knowledge on how to start building software ecosystems is still needed. The goal of this case study was to investigate activities and challenges in the planning phase of a Finnish software ecosystem. The case study was conducted by interviewing representatives of all six actors of the ecosystem and analyzing the material of the 12 planning workshops. The definition of a vision and objectives, the selection of actors, and the definition of a governance model were the main activities of the planning phase. It was also essential that the actors of the software ecosystem started the conceptualization of digital services and the definition of the business model together. One of the main challenges was that a clear strategy was not defined at the beginning of the planning phase. Furthermore, trust-building between the actors, different decision-making capabilities and a lack of the substance knowledge slowed down the planning phase. The actors also felt that much stronger leadership was needed.

The API has become a cornerstone of software ecosystems, providing ways to drive innovation inside and outside the organization. Because of this criticality, we should manage APIs. The purpose of this study is to identify and classify the challenges that organizations evolving into internal ecosystems are facing as they have to deal with APIs. We performed a qualitative research study on three Siemens internal ecosystems with different sizes, technologies, and age. The results reveal that even if we are talking about the API economy, organizations are struggling with different aspects of API management related to Business, Architecture, Process, and Organization. The challenges identified in this paper provide a basis for future research.

Context: Organizations are increasingly challenged by high market dynamics, rapidly evolving technologies and shifting user expectations. In consequence, many organizations are struggling with their ability to provide reliable product roadmaps by applying traditional roadmapping approaches. Currently, many companies are seeking opportunities to improve their product roadmapping practices and strive for new roadmapping approaches. A typical first step towards advancing the roadmapping capabilities of an organization is to assess the current situation. Therefore, the so-called maturity model DEEP for assessing the product roadmapping capabilities of companies operating in dynamic and uncertain environments has been developed and published by the authors. Objective: The aim of this article is to conduct an initial validation of the DEEP model in order to understand its applicability better and to see if important concepts are missing. In addition, the aim of this article is to evolve the model based on the findings from the initial validation. Method: The model has been given to practitioners such as product managers with the request to perform a self-assessment of the current product roadmapping practices in their company. Afterwards, interviews with each participant have been conducted in order to gain insights. Results: The initial validation revealed that some of the stages of the model need to be rearranged and minor usability issues were found. The overall structure of the model was well received. The study resulted in the development of the version 1.1 of the DEEP product roadmap maturity model which is also presented in this article.

Informed SaaS pricing decision-making requires the involvement of different business units and integrated pricing approaches. Achieving both appears to be challenging for a lot of SaaS providers, and despite its declared importance, pricing is one of the most under-managed business processes. Small and medium-sized companies do not have the resources for or the understanding of how to make informed decisions on pricing strategy and tactics. Pricing is a topic of interest in several research domains including economics, management science, digital and service marketing, and, increasingly, in software engineering. Still, the lack of integration between studies creates inconsistency in research. A comprehensive SaaS pricing body of knowledge is missing, as is a coherent action-oriented “Cookbook”. This multi-vocal literature review both brings together results from these research domains and matches practitioner expertise with academic research outcomes to promote the advancement of SaaS pricing theory and practice.

When companies opt to open source their software, they may choose to offer the project to an open source foundation. Donating the software to an open source foundation offers a number of advantages, such as access to the foundation’s existing tools and project management. However, in donating the software, the company relinquishes control of the software and grants other foundation members—including competitors—the same rights to the software. Using a multiple-case study research approach, this paper examines how foundations manage conflicts of interest in the open sourcing donation scenario. We find that foundations primarily use a set of well-defined mechanisms to prevent such conflicts from arising, and that the use of these mechanisms can depend on the foundation type.

Dynamic data and continuously evolving sets of records are essential for a wide variety of today’s data management applications. Such applications range from large, social, content-driven Internet applications, to highly focused data processing verticals like data intensive science, telecommunications and intelligence applications. However, the dynamic and multimodal nature of data makes it challenging to transform it into machine-readable and machine-interpretable forms. In this paper, we report on an action research study that we conducted in collaboration with a multinational company in the embedded systems domain. In our study, and in the context of a real-world industrial application of dynamic data management, we provide insights to data science community and research to guide discussions and future research into dynamic data management in embedded systems. Our study identifies the key challenges in the phases of data collection, data storage and data cleaning that can significantly impact the overall performance of the system.

Continuous innovation (CI) in large, established companies aiming to both produce incremental innovations as well as to create more radical ones is complex and complicated. It is affected by many simultaneous hard and soft factors and interrelationships. One suggested way how CI performance can potentially be improved is by increasing transparency in the innovation process, through which better employee participation to the process can possibly be achieved. Modern information/knowledge management and sharing IT tools can support that in practice. In this paper, we investigate those questions in an industrial software-intensive B2B company case. The company augmented its former, formal stage-gate based innovation process with new practices in order to accelerate the business innovation decision-making with validated information. We collected empirically rich qualitative and quantitative data and analyzed it to extract a set of statements grounded on the data. Those statements suggest that it is central to engage and connect right people and key information for effective and efficient idea generation, idea development, and business incubation. However, in different phases various stakeholder feedback and expert knowledge are critical for successful innovation progress. Increased transparency supported by integrated and versatile innovation, and knowledge management IT tools can intensify them. In effect, the clock speed of the organization for connecting people, ideas, knowledge (even tacit), and business decisions is accelerated. Overall the CI process should be flexible but at the same time it should frame the central direction. Consequently, it is hard to measure CI performance fully decisively with traditional KPIs.

The agility proposed by new software development practices such as Continuous Delivery and Continuous Deployment may introduce challenges to the teams who adopt such practices. One of these challenges is the change management process. The goal of this systematic literature mapping is to understand which change management practices are used in environments that adopted CDE or CD, focused on practices that could benefit application support teams, an important stakeholder in the software development life-cycle. Our study indicates the change management practices, in environments where CDE and CD have been adopted, have not been deeply explored and documented, an opportunity for future researches.

The deployment of production-quality ML solutions, even for simple applications, requires significant software engineering effort. Often, companies do not fully understand the consequences and the business impact of ML-based systems, prior to the development of these systems. To minimize investment risks while evaluating the potential business impact of an ML system, companies can utilize continuous experimentation techniques. Based on action research, we report on the experience of developing and deploying a business-oriented ML-based dynamic pricing system in collaboration with a home shopping e-commerce company using a continuous experimentation (CE) approach. We identified a set of generic challenges in ML development that we present together with tactics and opportunities.

Mobile app stores like Apple’s AppStore or Google’s PlayStore are highly competitive markets for third-party developers wanting to develop successful applications. During the development process, many developers focus on the multitude of product functions but neglect the business model as an equally important part. As a result, developers often fail to meet customer needs, leading to unnecessary development costs and poor market penetration. This, in turn, raises the question of how we intertwine the business model and product functions during the development process to ensure a better alignment between the two.In this paper, we show this intertwined development by adapting the concept of Twin Peaks to the business model and product functions. Based on feature modeling as an abstraction layer, we introduce the concept of a Business Model Decision Line (BMDL) to structure the business model decisions and their relation to product functions structured in a Software Product Line (SPL). The basis of our feature models is the analysis of top listed applications in the app stores of Apple and Google. To create and modify both models, we provide an incremental feature structuring and iterative feature selection process. This combination of abstraction layer and development process supports third-party developers to build successful applications both from a business and a product perspective.

In this multi-case study we report the findings from three software projects conducted with SCRUM agile development framework. Each project took approximately a little less than a year to design, develop and test before the launch to the user groups. All project vendors utilized SCRUM framework customized to suit their processes, and included customer as a participant in the overall process. Due to this fact, this study focuses on the role of the customer in daily life of an agile project. The findings show what is actually required from the customer – especially when the sprint length is only one week and the development process is very time-intensive. Although a one week sprint cycle can lead to improved efficiency it required a full time worker from the customer side and it burdened also the developers. Based on our observations, as the developer teams and customer were located in various places around Europe, smooth communication was a key for success. In all cases the asynchronous communication tools, such as Slack, were highly praised, although also direct communications were used to handle more complex issues. According to our findings, these agile projects did not have significant issues caused by the online communication being the preferred way of communication. All of the cases had difficulties in fitting the agile project to the fixed budget, but good collaboration, partnership and trust alleviated most of these problems.

This study examines the customers’ experience of value added they gain from the use of a cloud-based solution for documentation and quality management in construction industry. The industry is a laggard in the adoption of digital solutions. Currently it struggles with very low productivity increases, and the need to develop the operations to respond to new needs. Digitalizing documentation and potentially also quality management is one possibility for the industry towards better productivity. The empirical study was conducted through qualitative interviews with industry experts and organizations that have implemented a cloud-based solution for documentation and quality management. The findings of the study show that using a cloud-based solution for construction documentation generates numerous different kind of value in use benefits. In addition to the time savings in employees’ daily job, the use of the solution provides gains in documentation quality and contributes even to the company image for both the (potential) employees and external stakeholders. Most importantly, the use of the solution enhances keeping track of the big picture as it adds to the accessibility and transparency of the data. The industry experts envision that digitalized solutions can be used for developing completely new business models in the industry.

Cryptocurrencies and Initial Coin Offerings (ICO) are some of the more prominent examples of currently used blockchain technology applications. Especially software startups have leveraged ICOs to gain funding early on in their lifecycles, going on to develop and create new blockchain based applications. Recently, larger companies such as Facebook have also begun to show interest in cryptocurrency, although thus far not for funding purposes in the form of ICOs. In this paper, we investigate factors that positively affect the abilities of companies to meet their fundraising goals via ICOs. We first identify a set of factors from extant literature and then seek to further confirm the effect of these factors while uncovering new ones by means of a multiple case study of eight firms that have carried out an ICO with varying success. Based on the data, we highlight success factors for ICOs in funding use.

Digital and software-based solutions have been identified as key enablers of circular economy, a recently emerged phenomenon that promises more sustainable business through better systemic material efficiency. Opportunities reside on multiple implementation levels. For example, optimizing resource use within processes, engaging in business models enabled by software development, sharing information to optimize resource use on a network level, and creating infrastructures that support systemic tracking and optimization of resource usage.This conceptual paper contributes to both circular economy and information systems research by identifying the most prolific technologies underlying software-based solutions enabling circular economy. Furthermore, this paper discusses requirements and barriers for successful implementation of identified solutions residing on each of the application, network, and infrastructure levels, providing a framework for researchers analyzing digital solutions and software business in the context of circular economy, and for practitioners seeking to leverage the potential of digital technologies for their customers.

As Artificial Intelligence (AI) systems exert a growing influence on society, real-life incidents begin to underline the importance of AI Ethics. Though calls for more ethical AI systems have been voiced by scholars and the general public alike, few empirical studies on the topic exist. Similarly, few tools and methods designed for implementing AI ethics into practice currently exist. To provide empirical data into this on-going discussion, we empirically evaluate an existing method from the field of business ethics, the RESOLVEDD strategy, in the context of ethical system development. We evaluated RESOLVEDD by means of a multiple case study of five student projects where its use was given as one of the design requirements for the projects. One of our key findings is that, even though the use of the ethical method was forced upon the participants, its utilization nonetheless facilitated of ethical consideration in the projects. Specifically, it resulted in the developers displaying more responsibility, even though the use of the tool did not stem from intrinsic motivation.

Motivation behind electronic government (eGovernment) is generally creating of a better society. However, many eGovernment projects have failed due to the complex nature of these ecosystems. In the future eGovernment are starting to form larger data ecosystems due to initiatives such the European Single Market. The current trend of moving from national initiatives to international cooperation will make these projects even more complicated and thus, even more vulnerable to failures. Multiple large groups of stakeholders should be considered in the governance of these ecosystems, but there are little effective ways for that. It has been argued that values play an integral role in the success of eGovernment. Thus, in this paper we present a constructive analysis of values in eGovernment that aims to clarify the complexity around the matter. First, different levels and types of values affecting eGovernment are considered and then existing values guiding the governance of eGovernment are analysed. Based on these preliminary analyses it is noted, that there are some justified values, but more work is needed to create ethical governance model for eGovernment and data ecosystems that they are a part of to avoid failures and perhaps reach the goal of better society.

Much research have proven the advantages of innovation in education and training as well as of gamification in different areas of business and engaging people. These both concepts have been used in software implementation projects but still there is a knowledge gap on how they impact such projects. This explorative study aims at undertaking two experiments so as to reveal how educational innovation may impact the training process as part of a business software implementation project and how gamification may influence the testing phase and process of the same project. The experiments have been performed in an ERP implementation project. Before them, a literature review analyses the nature of educational innovation, gamification and ERP implementation to bridge the gap between these three concepts of this multidisciplinary approach for knowledge transfer between different management areas. The results of the experiments show concrete examples of game design elements and educational innovations for their application within training and testing phase of business software implementation project. The results of the experiments showed unconditionally the relevance of these two approaches in training and testing of business software.

It is not easy to provide real-world experience to students in an academic setting. When it comes to the development of a software startup, the connection with real users and customers is a must; otherwise, it becomes just a technical challenge. Furthermore, universities and the academic environment are paying more attention to this topic in the past years. One interesting work developed in this regard is the Challenge Based Startup Learning. In this sense, this paper aims at exploring, studying, and extending the Challenge Based Startup Learning Framework by running an expert panel. The idea behind this approach is to collect useful feedback in order to improve the framework to provide student with a better software startup development experience.

Startup education presence in Computer Science and Software Engineering curriculum has risen in the recent years. Currently, most reported courses focus on teaching innovation and business techniques and try to emulate real-world projects to convey the content. They have not focused on team composition which is a critical element for the success of startups since missing human capital increases the uncertainty involved in the process. In this paper, based on a literature review, we present a set of concepts about software startups team composition to be explored in a course. We also present a board game as a supplementary tool to convey these concepts. To evaluate the tool, we placed students in an artificial learning environment where they watched a video lesson about the topics and played the game. Then, participants answered a questionnaire about motivation, user experience, and perception of learning. The results indicate a first evidence of the value of the tool inducing a positive effect on learning as perceived by students.

Self-efficacy belief affects humans in life, action and work. Higher self-efficacy enables stronger contribution in fulfilling tasks, helping others in a team, and survive when facing obstacles and failures. Also creativity correlates to higher self-efficacy. At the same time, design is a powerful skill in note-making, improving the student’s understanding of the undergoing topic in a class. Note-making, when consisting of recorded writings, self-drawn images and other supportive subjects like structural analyses, charts, ad-hoc notes, detailed features and verbal links to related themes, forms a fundamental skill and ability in learning and applying new motifs and patterns. We executed during a design class an experiment with 22 students from various faculties at two universities by designing and creating visual notebooks. The students acted as designers and visualizers communicating to themselves and their teams with own creations. These notebooks were analyzed and reflected against the questionnaire results to evaluate the impact of the course in the progress in design skills and creativity.

Software engineer’s/developer’s competency has long been established as a key pillar for the development of software. Nevertheless, the satisfaction levels derived from using a competency needs more investigation. The aim of this paper is to propose a framework for identifying hard competencies and their satisfaction levels. The paper contributes to the software engineering competency research by highlighting the satisfaction levels of hard competence for the benefit of the educators (academia), software engineers and users of software competence (practitioner).

Learning from experience is essential for software startup teams. To obtain experiential learning, reflection should be conducted on experience. The existing research on reflection in software startups is much limited. In this study, we focused on reflection in software startup teams and identified formats, triggers and challenges used in such a context. To achieve this, we defined a conceptual framework of reflection. We conducted a multiple case study and analyzed the data obtained from two software startups. The initial finding shows that software startups do perform reflection of different types based on the factors like team size and collocation. We also found two new formats, three triggers and three challenges of reflection in software startups. Reflection sessions conducted by startups could mean tough moments, confrontations and sometimes involve the ego of team members. To conduct the session, it is important to be open, honest, raise key affair and straight to the point.

It is commonly claimed that the initial stages of any startup business are dominated by continuous, extended uncertainty, in an environment that has even been described as chaotic. Consequently, decisions are made in uncertain circumstances, so making the right decision is crucial to successful business. However, little currently exists in the way of empirical studies into this supposed uncertainty. In this paper, we study decision-making in early-stage software startups by means of a single, in-depth case study. Based on our data, we argue that software startups do not work in a chaotic environment, nor are they characterized by unique uncertainty unlike that experienced by other firms.

While business-to-customer (B2C) companies, in the telecom sector for instance, have been making use of customer churn prediction for many years, churn prediction in the business-to-business (B2B) domain receives much less attention in existing literature. Nevertheless, B2B-specific characteristics, such as a lower number of customers with much higher transactional values, indicate the importance of identifying potentially churning customers. To achieve this, we implemented a prediction model for customer churn within a B2B software product and derived a model based on the results. For one, we present an approach that enables the mapping of customer- and end-user-data based on “customer phases” which allows the prediction model to take all critical influencing factors into consideration. In addition to that, we introduce a B2B customer churn prediction process based on the proposed data mapping.

Crowdsourcing has emerged as a cost-efficient solution for companies to resolve certain tasks requiring vast amounts of human input. In order to motivate participants to harness their best efforts for the crowdsourcing task, companies are gamifying or creating complete games around crowdsourcing problems. The location-based game Ingress integrated the development of a geographically distributed database of points of interest in its game design. Players submitted and later peer-reviewed PoI candidates for Niantic for free, who then used the crowdsourced database as backbone for such popular games as Pokémon GO and Harry Potter: Wizards Unite. This study analyzes the solution in Ingress from two main perspectives: (1) how the game motivates players to participate in the crowdsourcing tasks and (2) how crowdsourcing fits into the game creator Niantic’s revenue model. The results show that Ingress players are provided multi-layered motivation to participate in crowdsourcing. The crowdsourcing tasks influence the game world, but are not limited inside it, and can be used elsewhere. Adopting crowdsourcing as a business strategy has served Niantic well, making Niantic an international multi-billion dollar company. Therefore it is predicted that more online multiplayer games implementing crowdsourcing as a revenue stream are likely to emerge in the near future.

The purpose of the paper is to empirically research what is the interconnection between the efforts of business organizations to manage their organizational innovativeness and using management information systems in their management and operations. The organizational innovativeness in the study is narrowed by the prism of innovative potential and innovative capabilities that are defined by the Company Innovative Leadership model. The scope of IT when it comes to business and IT alignment is seen from the usage of ERP, CRM and BI systems for information and process management of operations. These three management information systems act as tools for Business and IT Alignment in the study. The methodology employed in the study relied on 51 middle and high level management respondents who explained what are the possible linkages between innovation goals of organizations and application of information and process information systems. The key findings of the results are concrete identified aspects of organizational innovativeness that may rely on information and process information systems. The practical implication of the study is its possible use as a high-level tool for organizations on how to approach and to address their organizational innovativeness by the already used systems.

This paper presents a proposal of a Minimal Viable Development Process for Software Startups that can be used during the MVP development process. Defining a methodology is a major challenge for startups because they are creative, flexible, and reluctant to include bureaucratic measures in their day-to-day procedures that may disrupt their natural attributes. Thus, to make the process simple, we defined it in 3 main phases: requirements gathering, software development, and market validation.

Software startups are software-intensive early-stage companies that have high growth rates. Their time to market is often regarded as short and decisive in establishing their product/service success, thus leading to short-cuts in software engineering decisions. High accumulation of the technical debt at early stages has been documented from previous investigations. How startups rapidly becoming grownups perceive technical debt, make the primary goal of our study. We conducted semi-structured interviews with six technical and executive officers from five software startups, selected using purposive sampling. We identified four critical perceptions (managing, accepting, avoiding, ignoring technical debt) which permit them to make technical debt trade-offs. We also found that no one size fits all. Startups need to make deliberate educated decisions on how to use technical debt in their advantage.

Current literature suggests that engineering activities of software engineering and software startup engineering differ. Thus, there is the need to elicit competencies specific for software startup engineering. This paper proposes a model that provides the various types of competencies and their respective relevance at the various stages of software startup evolution.

The business domain of software development growth increasingly during 2018 and while software companies in Finland are taking benefit of this momentum, they are facing multiple internal and external challenges. We constructed annual software business survey for 99 enterprise to micro-size software companies in Finland. Based on our survey, software development firms aim at growing rather than improving efficiency or changing focus. The focus remains on strengthening the current business instead of aligning it with the market transition, although the lack of competence and resources is remarkable. This poster paper gives a prompt overview of the Finnish software business domain and how software companies are encountering it.

We have been teaching an experiential-based course for fist year master students. In the last two years, we have added to the course external activities such as Hackathon and Bootcamp. These external activities helped students internalize how important are soft skills and involvement of external stakeholders to succeed in developing relevant startup projects. This year, we wanted to evaluate if students were getting what we declared. We conducted a survey on students’ perception of different dimensions: soft skills challenges (teamwork, communication with stakeholders, presentation, negotiation, and innovation), technical challenges and project management (PM) challenges, before and at the end of the Bootcamp days. We found out that the mean values regarding soft skill challenges and project management vary, while values regarding technical challenge have not changed before and after Bootcamp. The overall outcomes of the study contribute to conceptualizing an early model integrating student startup formation with course learning outcomes.

Artificial Intelligence (AI) Ethics have steadily gained attention following various real-world incidents surrounding both purely digital and cyber-physical AI systems. Concerns have been raised over the ethical aspects of these systems for example in relation to data privacy, or material harm in the case of cyber-physical systems. Though academic activity in the area has grown recently, much of the current corpus consists of theoretical and conceptual studies. Attempts to bring this on-going discussion into practice have been primarily made in the form of various guidelines for ethical development of AI systems. However, these guidelines have not been adopted out on the field. The current situation in the area calls for more actionable methods for AI ethics, focusing on the point of view of developers. In this paper, we discuss current methods for implementing ethics in different contexts and then provide an introduction to a tutorial on a developer-focused method for implementing AI ethics, the Ethics Card Deck.