Towards #consistentAI Position Paper

Dutta, Debojyoti; Saha, Amit; George, Johnu; Huang, Xinyuan; Pydipaty, Ramdoot; Kamath, P.; Tucker, Lew

doi:10.1109/ai4i.2018.8665683

Cited by 1 publication

(3 citation statements)

References 1 publication

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It is interesting to note that some of the presented requirements correspond with identified requirements on Industrial AI correspond to research fields recently identified for Scientific Machine Learning [33]. We foresee future developments of Industrial AI in the areas of i) production system autonomy [18], ii) product life cycle management [15], especially because AI life cycles will become more complex to manage [23], iii) virtual industrial assistants [34], iv) explainable AI [35] and v) the seamless fusion of different data pools in production sites.…”

Section: Discussionmentioning

confidence: 62%

“…The presented list of requirements may not be conclusive but covers many aspects specific to Industrial AI solutions. Further requirements left out in the presented list may cover topics such as data / analytics privacy [30], ethical implication [31], potential malicious use of AI [32] as well as AI-vendor lock-in [23].…”

Section: Discussionmentioning

confidence: 99%

“…The user of AI-based production systems will most-likely not have a mathematical or computer science education and thus also the usage and operation of industrial AI systems shall be simple and hide all otherwise required technical complexity. A more simplistic design of Industrial AI solution will also lead to greater robustness of the system [23].…”

Section: )mentioning

confidence: 99%

See 2 more Smart Citations

Proposal for requirements on industrial AI solutions

Hoffmann¹,

Drath

Ganz

2020

Technologien Für Die Intelligente Automation

View full text Add to dashboard Cite

The rise of artificial intelligence (AI) promises productivity gains in industrial practice. While IT technology offers a variety of technological advances, plant owners strive for stability and robustness of the production process. To overcome this tension field, we propose a set of 16 requirements for the development of industrial AI solutions to foster i) the adaptation process, ii) support the solution engineering and iii) ease the embedding into the existing system landscape while respecting iv) safety aspects to build up v) trust into industrial AI solutions. The proposed requirements can guide industrial stakeholders to focus on the right solution approach for specific production challenges and support them in voicing their own needs towards novel AI solutions. This will help AI developers to speed up time-to-market as well as to increase market acceptance of industrial AI solutions. Overall, specifying requirements on industrial AI will foster the acceptance and utilization rates of AI solutions in industrial practice.

show abstract