PressClub Global · Article.
Seven principles for AI: BMW Group sets out code of ethics for the use of artificial intelligence.
Mon Oct 12 09:00:00 CEST 2020 Press Kit
+++ AI already widely used within the company +++ Over 400 use cases throughout the value chain +++ Code of ethics underpins the increased use of AI technologies +++
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BMW Group
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Martin Tholund
BMW Group
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Munich. The use of artificial intelligence (AI) is a central element of the digital transformation process at the BMW Group. The BMW Group already uses AI throughout the value chain to generate added value for customers, products, employees and processes.
Michael Würtenberger, Head of “Project AI”: “Artificial intelligence is the key technology in the process of digital transformation. But for us the focus remains on people. AI supports our employees and improves the customer experience. We are proceeding purposefully and with caution in the expansion of AI applications within the company. The seven principles for AI at the BMW Group provide the basis for our approach.”
The BMW Group continues to follow global developments in terms of both technological innovations and regulatory and ethical issues. Together with other companies and organisations, the BMW Group is involved in shaping and developing a set of rules for working with AI, and the company has taken an active role in the European Commission’s ongoing consultation process.
Building on the fundamental requirements formulated by the EU for trustworthy AI, the BMW Group has worked out seven basic principles covering the use of AI within the company. These will be continuously refined and adapted as required according to the multi-layered application of AI across all areas of the company. In this way, the BMW Group will pave the way for extending the use of AI and increase awareness among its employees of the need for sensitivity when working with AI technologies.
Seven principles covering the development and application of artificial intelligence at the BMW Group:
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Human agency and oversight.
The BMW Group implements appropriate human monitoring of decisions made by AI applications and considers possible ways that humans can overrule algorithmic decisions.
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Technical robustness and safety.
The BMW Group aims to develop robust AI applications and observes the applicable safety standards designed to decrease the risk of unintended consequences and errors.
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Privacy and data governance.
The BMW Group extends its state-of-the-art data privacy and data security measures to cover storage and processing in AI applications.
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Transparency.
The BMW Group aims for explainability of AI applications and open communication where respective technologies are used.
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Diversity, non-discrimination and fairness.
The BMW Group respects human dignity and therefore sets out to build fair AI applications. This includes preventing non-compliance by AI applications.
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Environmental and societal well-being.
The BMW Group is committed to developing and using AI applications that promote the well-being of customers, employees and partners. This aligns with the BMW Group’s goals in the areas of human rights and sustainability, which includes climate change and environmental protection.
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Accountability.
The BMW Group’s AI applications should be implemented so they work responsibly. The BMW Group will identify, assess, report and mitigate risks, in accordance with good corporate governance.
Overall centre of competence for the company: “Project
AI”.
“Project AI” was launched in 2018 to ensure that AI
technologies are used ethically and efficiently. As the BMW Group’s
centre of competence for data analytics and machine learning, it
ensures rapid knowledge and technology sharing across the company.
Project AI therefore plays a key role in the ongoing process of
digital transformation at the BMW Group and supports the efficient
development and scaling of smart data and AI technologies. One of the
developments to come out of Project AI is a portfolio tool which
creates transparency in the company-wide application of technologies
making data-driven decisions. This D³ (Data Driven Decisions) portfolio
currently spans 400 use cases, of which more than 50 are available for
regular operation.
WHERE IS THE BMW GROUP ALREADY USING AI?
USE CASES FROM
DIFFERENT AREAS OF THE COMPANY.
The following examples show that Project AI pushes the BMW Group forward with AI focused, company-wide networking and knowledge transfer. The fundamentally identical technology forms of AI can generate added value for customers, employees and business processes. For example, the customer benefits from natural language processing (NLP) with the Intelligent Personal Assistant directly in the vehicle and employees are supported with translation tools and context-processing assistants in administrative processes. Intelligent data analysis and machine learning are used to optimise energy management both in buildings and in vehicles. And image processing AI relieves both the customer with driver assistance systems from monotonous driving tasks and employees in production from monotonous processing steps.
E XAMPLES FROM RESEARCH & DEVELOPMENT.
AI-based energy management in vehicles.
A
vehicle contains a large number of electric consumers, such as seat
heating, the entertainment system, the air conditioning, etc. In many
cases, the driver is not aware that using these consumers also has an
effect on CO2 emissions and/or the range of the vehicle. AI
experts at the BMW Group are conducting R&D work on AI-based
software for in-vehicle energy management. Taking user behaviour and
route information as a basis, the system learns how to adjust energy
consumption in the car as effectively as possible to the driver’s
requirements and the need for energy efficiency. In this way,
CO2 emissions can be reduced, energy saved and operating
range increased.
Acoustic analytics: sensory enhancement in the sensor model
for automated driving functions.
The BMW Group is
taking an all-encompassing approach to monitoring the vehicle
environment. One of the areas the company is exploring to this end is
how acoustic signal processing can be added to the AI sensor fusion.
Incorporating auditory perception can have benefits for urban
scenarios, in particular, going forward.
AI in requirements management.
At the BMW Group there are over 33,000 requirement specification
documents containing more than 30 million individual requirements for
vehicles, components and characteristics. That’s an enormous amount of
data. AI technologies can help employees to process large quantities
of data more quickly and carefully. Here, an application has been
developed which uses natural language processing methods to improve
the quality and analysis of individual requirements in specification
documents. The web-based tool allows thousands of requirements to be
automatically translated and checked – in real time – for linguistic
quality, similarity and consistency.
EXAMPLES FROM SUPPLY CHAIN MANAGEMENT AND LOGISTICS.
Integrating AI with facility and robot control systems.
The first smart AI control application at the BMW
Group celebrated its premiere at the BMW Group’s Steyr plant. This
application speeds up logistics processes by preventing the
unnecessary transport of empty containers on conveyor belts. To this
end, the containers pass through a camera station. Using stored image
data marked by employees, the AI application recognises if a container
needs to be lashed onto a pallet or whether – in the case of large,
stable boxes – no additional securing is required. If no lashing is
required, the AI application directs a container by the shortest route
to the removal station for the forklift truck.
Besides the application in Steyr, AI can be found in numerous other logistics innovations at the BMW Group. It also supports virtual layout planning, which creates high-resolution 3D scans of buildings and factories. AI ultimately contributes to the recognition of individual objects in the 3D scans, such as containers, building structures and machines. In this way, robotics applications out-perform the technology used previously in their coordination skills and ability to recognise people and objects. Navigation improvements enable obstacles such as forklift trucks, tugger trains and employees to be detected more quickly and clearly, and alternative routes to be calculated within milliseconds. The AI-based technology helps the robotics applications to learn and apply different reactions to people and objects.
EXAMPLES FROM PRODUCTION.
Since 2018, the BMW Group has been using various AI applications in series production. One focus is automated image recognition: In these processes, AI evaluates component images in ongoing production and compares them in milliseconds to hundreds of other images of the same sequence. This way, the AI application determines deviations from the standard in real time and checks, for instance, whether all required parts have been mounted and whether they are mounted in the right place. At the BMW Group, flexible, cost-effective, AI-based applications are gradually replacing permanently installed camera portals. Implementation is comparatively simple. A mobile standard camera is all that is needed to take the relevant pictures in the production hall. The AI solution can be set up quickly too. Employees take pictures of the component from different angles and mark potential deviations on the images. This way, they create an image database in order to build a neural network, which can later evaluate the images without human intervention.
Name plate checks.
In the final inspection area
at the BMW Group’s Dingolfing plant, an AI application compares the
vehicle order data with a live image of the newly produced car’s model
badge. Model designation badges and other identification plates (such
as “xDrive” for all-wheel drive vehicles and all generally approved
combinations) are stored in the image database. If the live image and
order data don’t correspond – if a designation is missing, for example
– the final inspection team receives a notification. You can find more
information here.
Dust particle analysis in the paint shop.
AI can control the operation of highly sensitive automotive
production equipment even more precisely, as a pilot project in the
paint shop at the BMW Group’s Munich plant has shown. If levels of
dust increase due to the time of year or a sustained dry period, the
algorithm picks up on the trend at an early stage and brings forward
the timing of a filter change, for example. Working in conjunction
with other analysis tools, additional patterns can be recognised.
Another result of the analysis might be that fine adjustments need to
be made to the machine using ostrich feathers to remove dust particles
from the car body. The BMW Group’s AI experts see great potential in
dust particle analysis. Supplied with information from numerous
sensors and data from surface inspection, the algorithm monitors more
than 160 features of the body and can predict the quality of a paint
application with great accuracy. You can find more information here.
AI control application in the press shop reliably prevents pseudo-defects.
At the press shop, flat sheet metal parts are turned
into high-precision components for the car body. Dust particles or oil
residues that remain on the components after forming can easily be
confused with very fine cracks, which occur in rare cases during the
process. Previous camera-based quality control systems at the BMW
Group’s plant in Dingolfing occasionally also identified these
pseudo-defects (deviations from the target values, but with no actual
fault). With the new AI application, these pseudo-defects no longer
occur because the neural network can access around 100 real images per
feature – i.e. around 100 images of the perfect component, 100 images
with dust particles, another 100 images with oil droplets on the
component, etc. This is particularly relevant in the case of the
visually close calls that have previously led to pseudo-defects. You
can find more information here.
BMW won the Connected Car Pioneer Award 2020 in recognition of its versatile use of AI in production.
EXAMPLES FROM AFTERSALES & CUSTOMER SERVICE.
AI at dealer service desks.
If a BMW customer
visits a dealer reporting a problem with their car, the problem needs
to be identified quickly and the right solution found reliably. To
help them do this, the service employee has the use of a knowledge
database, which has been expanded using a powerful software stack to
include both an intelligent and scalable search facility and AI (for
processing problem cases and knowledge data). AI incorporates context
information into the search process, enabling it to flag up identical
and similar cases. Added to which, an automatic translation function
breaks down the language barrier in the fault analysis process.
AI-based customer interaction in WeChat.
Chatbots help to significantly increase the quality and
availability of customer service. In China, BMW Financial Services
offers its customers an AI-based chatbot via the widely used WeChat
app. The chatbot allows customers to ask questions regarding their
personal finance agreement or make changes to their agreement. These
bots are first trained to deal with the topics for which most
questions are received by the call centre. If the chatbot cannot
answer a question, the enquiry is passed to a human member of staff.
This means that customers’ most frequently asked questions can be
answered quickly and with a consistently high level of quality around
the clock.
EXAMPLE IN BUILDINGS MANAGEMENT.
Increasing energy efficiency in BMW Group
buildings.
Since 2006 the BMW Group has been able to
consistently increase energy efficiency at its locations around the
world. It has now reached such a high level that identifying further
potential for improvement using conventional means is getting more and
more difficult. This is where the use of smart data and AI comes into
play. The BMW Group systematically processes all the energy-relevant
data at its locations so previously undiscovered energy consumption
patterns can be established using AI. Weather-related data can also be
incorporated into this process, enabling buildings to be heated and
cooled more intelligently and efficiently. In a pilot project in
Munich, this approach has allowed approximately 1,200 MWh of thermal
energy to be saved annually in the IT centre. This equates to the
energy consumption of approximately 60 family homes. This experience
and a rigorous process of data collection and analysis have also led
to positive energy efficiency results at office buildings such as the
BMW four-cylinder building, FIZ Projekthaus, Campus Freimann and the
dynamics centre at Dingolfing.
EXAMPLE FOR ADMINISTRATION & SUPPORT FUNCTIONS.
Customized Machine Translation (CMT) – machine translation
that learns the language of BMW.
The BMW Group is a
multinational company with a presence in over 100 countries. Its
customers, dealers and employees speak hundreds of languages and there
is an enormous daily influx of multilingual texts from external
sources. Human translation of all multilingual data does not make
sense due to the volume and costs involved. Freely available
translation solutions are not permitted for reasons of information
protection and often fail to provide the correct translation of
technical terms and formulations – the correct “BMW language”. With
this in mind, BMW Group IT has developed its own translation solution
specialising in BMW texts. BMW Group employees are now feeding over
2,000 sentences into the system every day.
EXAMPLES FOR CUSTOMER AND VEHICLE FUNCTIONS.
Driver assistance.
AI is the key to automated
driving – and is already present in current driver assistance systems
such as Driving Assistant Professional. Automation-based functions
help customers to drive safely, park and stay connected. On motorways,
they can take over longitudinal and lateral guidance of the vehicle
for extended periods. The customer remains responsible for the car,
but their task is now only to monitor what is happening.
BMW Intelligent Personal Assistant.
The BMW Group has revolutionised driving pleasure with the BMW
Intelligent Personal Assistant. Introduced in 2019, this intelligent
digital on-board companion responds to the prompt “Hey BMW”. The BMW
Intelligent Personal Assistant increasingly allows the car to be
operated, functions to be accessed and information obtained by voice
command alone. This technology enables direct communication and
natural interaction with the vehicle – helped by AI.
Article Offline Attachments.
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BMW Group Code of ethics for AI - Long Version PDF, EN, 258.47 KB
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BMW Group Code of Ethics for AI - Short Version PDF, EN, 249.38 KB