The Bias Against Bias: Using Bias Intentionally in Artificial Intelligence

In the last few hours alone, you’ve likely encountered AI, probably some positive experiences as well as frustrating ones. From streaming services recommending your next favorite show to product suggestions on retail sites, almost every digital interaction revolves around AI technology, making the task faster. And if you run into a problem or have a question, you can usually reach out to chat with a customer service representative, which is actually an AI-based chatbot. Because AI integration is relatively seamless and easy for business, many people don’t even realize that their wants and needs are predicted by software.

Although AI can be beneficial to business, concerns about bias are continually raised because of its association to fairness and non-discrimination. This stems from the assumption that bias is always negative. This is not true. In fact, intentionally using bias is a key element of effective data-driven AI systems.

Take for example the retail sector. Many retailers instantly invite you to apply for a store credit card when you make a purchase and meet certain credit-scoring criteria. Of course, the retailer wants to make sure customers can repay debt, so the algorithmic decision making turns down customers who are likely unable to pay down credit.

“We expect that the algorithm is biased against people who cannot pay, which most people would not consider a problem. But if the bias were against males or females, then that would be unwanted bias,” says Christopher Clifton, Vice Chair of the Algorithmic Bias Working Group. “However, getting rid of all bias completely means making random decisions, similar to flipping a coin, which isn’t how we want these systems to operate.”

However, AI readily perpetuates human biases. If a company has predominantly hired men for specific positions and then uses AI technology trained on past hires to evaluate applicants, the data fed into the algorithm will be biased toward men. Because the current hiring managers are likely not aware of the bias in the algorithm, they unintentionally pass over qualified female candidates, which unfairly discriminates against women.

As the IEEE P7003 Working Group began addressing the impact of bias in technology, the team quickly realized that their goal was not eliminating bias in AI systems but rather addressing the bias against bias to then help organizations use bias intentionally.

Under the umbrella of bias in AI, the working group determined that there are basically three sources of bias:

• Bias by the algorithm developers: This happens based on the choice of an optimization target, for example, if a worker-management algorithm optimizes processes for maximum worker output, but doesn’t maximize worker health.
• Bias within the system itself: The system itself expresses differences in performance levels for certain categories, such as higher failures in facial recognition based on race and gender.
• Bias by users of the system: Users can interpret and act upon the output generated by the algorithm in a biased manner. For example, confirmation bias happens when the output of ChatGPT says something that you already believe, or want to believe, and you accept it without checking whether it is true.

Additionally, the context of a biased decision makes a big difference. It may be fair in one situation, but unfair in another, for example while the bias against people who cannot pay is critical to the success of the business, a bias based on gender or race, whether intentional or unintentional, would be a serious issue.

Ansgar Koene, former Chair of the Working Group, says the key is ensuring that bias in the system is performing a function for what the system is designed to do.

“It’s important that the differentiation for whether it decides on option one or option two be based on factors in the input data that are actually relevant to the task,” says Koene. “If there is a difference in the outputs for each decision that can not be traced back to task-relevant differences in the input, it means it’s likely unwanted bias.”

The goal of IEEE P7003 is to generate awareness about AI systems and bias so that users and creators can evaluate if a system is actually performing the tasks that they want it to perform. To reduce unintentional bias, organizations need to fully understand the context in which the system is being created and how the stakeholders are impacted by the system. Additionally, you should know the actual task you’re asking the system to do and make sure the results fit with the desired tasks.

“It’s not the algorithm’s fault that there are problems with bias. Humans are biased, and bias can be a good thing or a bad thing—not because bias is good or bad in itself, but because of our intention. For example, an app designed to help women manage their health, should be biased towards women,” according to Working Group member Clare James.

The P7003 Working Group introduced the concept of a Bias Profile as part of the draft standard to help stakeholders evaluate and consider their processes to determine the impact and risk of bias. The profile helps to clarify the conceptualization of the system’s intention, as well as understand all the stakeholders who either use the system or would be impacted by it. Based on the resulting bias profile, an organization can assess if they need to fix the algorithm or stop using the system entirely.

“Some companies may initially find the process of the P7003 standard challenging to their self-image because it requires them to look closely at the impact their systems are having. Are they really serving people with their product or service?” says James.

Many organizations create an algorithm during the initial development of a system and evaluate it for bias, but do not go back to revisit it. However, the P7003 process should be repeated at regular intervals throughout the system life cycle, especially during the operation and maintenance stage, because how people use the system, as well as the population involved, naturally evolves over time. Additionally, organizations should revisit the profile if they deploy the system into a new context. If you train a system on 10-year-old data, it’s probably not going to be accurate or a reflection of the current situation.

As part of ensuring that systems do not have unwanted bias, organizations need diverse teams with multiple perspectives. Harvard University found that the accuracy of facial recognition software varies significantly by race, with the lowest accuracy for people who are female, Black, and 18-30 years old. Often systems are trained with photos of white males, which makes it less likely to recognize people of color. Errors in facial recognition systems can have significant consequences, especially with law enforcement heavily using the technology.

Gerlinde Weger, Chair of the Working Group, says that the bias in facial recognition systems was likely not intentional. Still, the result was that the system did not have the capability to recognize all types of stakeholders. She says it’s likely that a more diverse development team would have discovered this bias before the launch.

“Systems need to recognize attribute intersectionality, meaning how systems work together, to create a true stakeholder overview, not just a collection of bits and bytes,” says Weger. “Humans will always be impacted by and influence bias. With P7003 we aim to help minimize harms arising from unwanted bias.”

As AI becomes even more integrated into our systems and processes, algorithmic bias will have critical and widespread effects. By educating developers and developing a standard to increase the understanding of the intentionality of bias, IEEE SA can help transform issues of AI into positive assets.

While developing the standard, the Working Group sought input from a wider audience and community, through raising awareness of the project at conferences, working with legal experts, and running multiple surveys of the working group composition. The team established a balance not just with regard to geography or gender, but also academia, industry, and civil society. Additionally, they ensured that the working group included participants from different disciplines, including computer science, social sciences, and law.

The Working Group continues to need professionals in all industries and roles to focus on this issue. Learn about how to join the IEEE Algorithmic Bias Working Group.

Wi-Fi technology is based on the IEEE 802.11™ series of wireless connectivity standards which have revolutionized how we communicate and access information. Billions of Wi-Fi devices are in use worldwide today, dramatically impacting how individuals, businesses, governments, and societies interact. It is no exaggeration to say that the IEEE 802.11 series of standards has helped bring about inexpensive, equitable internet access globally.

In recognition of the Internet’s 40^th anniversary, we take a look at how the IEEE 802.11 series has driven the evolution of Wi-Fi technology and how new additions to the series will enable greater Wi-Fi capabilities, making innovative new applications possible.

Wi-Fi, a wireless local area network (WLAN) technology that enables digital devices within a certain area to communicate via radio waves, is so often and universally used today that it’s hard to remember a time when it didn’t exist. But in reality, that wasn’t so long ago.

Wi-Fi first came onto the market in 1997 when the pioneering IEEE 802.11 technical standard was published, enabling wireless data transmission at up to 2 Mbit/s using an unlicensed 2.4 GHz radio spectrum. Its major commercial breakthrough came in 1999 when Apple introduced the first mass-marketed consumer products with Wi-Fi connectivity, its AirPort wireless base station, and iBook. Thanks to the then-new IEEE 802.11b™ amendment to the original Wi-Fi standard, theoretical data rates up to 11 Mbit/s became possible.

Soon thereafter, Apple launched AirPort based on IEEE 802.11b, which kick started the wireless revolution. While that was true, what made that revolution possible in the first place was the IEEE 802.11 standards family.

Since then, the ongoing evolution of IEEE 802.11 Wi-Fi standards has led to much faster data transmission rates, longer ranges, and more reliable and secure connections. All IEEE 802.11 standard amendments are constructed in a manner such that devices which operate according to their specifications will be backward compatible with earlier versions so that any modern IEEE 802.11-based device can communicate with older products.

Along the way, a naming convention was developed by the Wi-Fi Alliance (“Wi-Fi #”) to help the general public better distinguish between various IEEE 802.11 implementations:

• IEEE 802.11™ is the pioneering 2.4 GHz Wi-Fi standard mentioned above from 1997, and it is still referred to by that nomenclature. This standard and its subsequent amendments are the basis for Wi-Fi wireless networks and represent the world’s most widely used wireless computer networking protocols.
• IEEE 802.11b™, or Wi-Fi 1, was introduced to the market in 1999 with Apple’s announcement. It also operated at 2.4 GHz, but to reduce interference from microwave ovens, cordless phones, baby monitors, and other sources, and to achieve higher data rates, it incorporated modulation schemes called direct-sequence spread spectrum/complementary code keying (DSSS/CCK). Wi-Fi 1 enabled wireless communications at distances of ~38m indoors and ~140m outdoors.
• IEEE 802.11a™, or Wi-Fi 2, also introduced in 1999, was the successor to IEEE 802.11b. It was the first Wi-Fi specification to feature a multi-carrier modulation scheme (OFDM) to support high data rates, unlike Wi-Fi 1’s single-carrier design. It supported 5 GHz operation and its 20 MHz bandwidth supported multiple data rates.
• IEEE 802.11g™, or Wi-Fi 3, was introduced in 2003. It allowed for faster data rates of up to 54 Mbit/s in the same 2.4 GHz frequency band as IEEE 802.11b, thanks to an OFDM multi-carrier modulation scheme and other enhancements. This was appealing to mass market users, as 2.4 GHz devices were less expensive than 5 GHz devices.
• IEEE 802.11n™, or Wi-Fi 4, was introduced in 2009 to support the 2.4 GHz and 5GHz frequency bands, with up to 600 Mbit/s data rates, multiple channels within each frequency band, and other features. IEEE 802.11n data throughputs enabled the use of WLAN networks in place of wired networks, a significant feature enabling new use cases and reduced operational costs for end users and IT organizations.
• IEEE 802.11ac™, or Wi-Fi 5, was introduced in 2013 to support data rates at up to 3.5 Gbit/s, with still-greater bandwidth, additional channels, better modulation, and other features. It was the first Wi-Fi standard to enable the use of multiple input/multiple output (MIMO) technology so that multiple antennas could be used on both sending and receiving devices to reduce errors and boost speed.

IEEE 802.11ax™, or Wi-Fi 6, is the most recent standard in the series, published in 2021, and devices based on it are now being deployed in billions of devices per year.

Although its theoretical data rate is 9.6 Gbit/s, this standard isn’t primarily about boosting Wi-Fi speeds per se. Rather, it addresses the fact that Wi-Fi usage is now so pervasive that network performance can be degraded in areas of dense Wi-Fi traffic, such as sports stadiums, concert halls, and public transportation hubs, and more and more even in our homes where routers must communicate with a growing number of digital gadgets simultaneously.

IEEE 802.11ax offers many enhancements. It employs a multi-user mechanism that allows the 9.6 Gbit/s data rate to be split among various devices. It also supports routers sending data to multiple devices in one broadcast frame over the air, and it lets Wi-Fi devices schedule transmissions to the router. Mechanisms to support longer-range outdoor operations are also added.

Collectively, these features improve aggregate throughput and support the increasing use of Wi-Fi in data-heavy situations and in applications such as video and cloud access, where real-time performance and low power consumption for battery-powered devices are required. In particular, high-definition video is expected to be the dominant type of traffic in many forthcoming Wi-Fi deployments.

IEEE P802.11be™, or Wi-Fi 7, is now under development at the IEEE Standards Association (IEEE SA) by a group of technical and industry experts, with an estimated completion sometime in 2024.

This standard represents a major evolutionary milestone in Wi-Fi technology, with 4x faster data rates (~40 Gbit/s) and twice the bandwidth (320 MHz channels vs. 160 MHz channels for Wi-Fi 6). It also supports more efficient and reliable use of available and contiguous spectrum through multi-band/multi-channel aggregation and other means. The standard features numerous enhancements to MIMO protocols and many other advancements and refinements of existing Wi-Fi capabilities.

The result of all these technical improvements is that to the user, Wi-Fi 7 technology will be much faster, have much lower latency, will support many more devices, and will perform much better in congested Wi-Fi spaces and where Wi-Fi networks overlap.

But that’s not all.

IEEE P802.11be, along with IEEE 802.11ax and future iterations of IEEE 802.11 standards, also could support many next-generation Wi-Fi applications. The IEEE 802.11 Working Group has established several special-interest groups to investigate many of them. Here are a few examples:

• Battery-Free, Ambient Power-Enabled Internet of Things (IoT) Networks – Ambient power refers to energy harvested from the environment – such as heat – that is converted to electricity. It could be used to power distributed IoT devices, leading to battery-free, more environmentally friendly IoT systems with less need for maintenance. Battery-free IoT networks could benefit multiple industries, including agriculture, smart grid, mining, manufacturing, logistics, smart home, transportation, and more. Studies are underway to examine the use cases, functional requirements, and technical feasibility of adding features to the IEEE 802.11 series to support ambient power-enabled IoT devices.
• Augmented/Virtual Reality (AR/VR) and the Metaverse – These are real-time applications that require extremely high data throughput and ultra-low latency. Users of these fast-growing consumer technologies are now in much greater need of faster, smoother, and more reliable Wi-Fi networks. The IEEE 802.11 Extremely High Throughput Study Group has been established to explore new IEEE 802.11 features for bands between 1 and 7.125 GHz that would increase peak throughput to support these demanding applications.
• Artificial Intelligence/Machine Learning (AI/ML) – The use of AI/ML techniques has exploded in recent years, and they touch virtually every area of human endeavor. AI/ML algorithms require a large amount of data to move between distributed data sources such as cameras, smartphones, and gaming devices, and a centralized server, where the data is analyzed. To address this need, new AI/ML algorithms have been developed that allow more analysis at the source, reducing the amount of data a network needs to carry. IEEE 802.11-based Wi-Fi networks carry an extensive and growing amount of data, making it possible to leverage new AI/ML algorithms, such as federated learning, to improve Wi-Fi performance and user experiences. A special interest group within the IEEE 802.11 WG is now investigating this idea.

Technology has become much more complex in the decades since the initial IEEE 802.11 standard was published, and the enduring value of that series of standards is a tribute to the global innovators who have contributed to it over the years.

As Wi-Fi networks continue to progress on multiple fronts, so will IEEE Standards, to help to bring out the full potential of Wi-Fi technology and serve the future industry and human needs.

Learn more and join our efforts to continue the evolution of this groundbreaking technology, which has given the gift of connectivity to the world.

When IEEE Standards Association launched the IEEE SA Interactive Soccer Stadium to coincide with the 2022 FIFA World Cup, it was clear there was wider interest in more real-world visualization of technology standards. We’re proud to announce that this stadium is now part of an encompassing experience that has been developed to demonstrate the applicability and breadth of IEEE Standards — the IEEE SA Interactive Cityscape.

From the internet to health care, and the smart grid to transportation, technology standards set the framework to keep technology innovating. By the time you’ve sat at your computer today to read this, you’ve interacted with dozens of technology standards, perhaps without even knowing it. This cityscape gives you a chance to learn about some of the many IEEE Standards that help create efficient, sustainable, and smart communities.

Start your tour with a birds-eye view of the city; you’ll see an amusement park, a grocery store, a solar rooftop, and a shipping port. As you move through the key landmarks, you’ll have an opportunity to read about how life meets standards (and occasionally, standards meet life).

Explore the interactive cityscape and see for yourself how technologies enabled by IEEE Standards are reimagining what we thought possible.

Learn more about IEEE Standards in everyday life at Standards in Action

The annual World Summit on the Information Society (WSIS) Forum brings together the largest gathering of the Information and Communications Technologies (ICT) community, which focuses on making the information society accessible to all. The WSIS Forum provides an opportunity for multi-stakeholder cooperation in providing meaningful connections to the information society and allows IEEE to showcase its work in support of sustainability.

The 2023 WSIS Forum was held 11-17 March with 2700 participants from over 150 countries attending 250 onsite and remote sessions. Many participants stopped by the IEEE booth to learn about IEEE’s work in contributing to the advancement of the UN Sustainable Development Goals (SDGs).

The IEEE theme for the forum was “Sustainable Stewardship Through Standards Development and Application”. From the IEEE Thematic Workshop on Standards and Sustainability to the Knowledge Café discussion on Beyond Planet Positive 2030, all the IEEE volunteers who attended successfully shared the work their standards groups are doing to support advancing technology for humanity.

Find a full list of IEEE-organized events at the 2023 WSIS Forum here.

The IEEE Thematic Workshop “Supporting the Transition to a Stronger, Greener, and Sustainable Future through Standards and Best Practices” focused on best practices and standards for addressing sustainability, environmental stewardship, and climate change challenges. Raised in the discussion were IEEE Standard P7800™ for Addressing Sustainability, Environmental Stewardship and Climate Change Challenges in Professional Practice, and IEEE P7010.1™ on Environmental Social Governance (ESG) and Social Development Goal (SDG) Action Implementation and Advancing Corporate Social Responsibility. It featured a panel comprised of the following IEEE volunteers and staff:

Maike Luiken, Chair, IEEE P7800™ Addressing Sustainability, Environmental Stewardship and Climate Change, Chair, IEEE Planet Positive 2030 Initiative
Ruth Lewis, Chair, IEEE Society for Social Implications of Technology (SSIT) Standards Committee
Deborah Hagar, Chair, IEEE P7010.1™ Advancing Corporate ESG and Social Responsibility
Christopher Whitt, President, IEEE Oceanic Engineering Society
Karen Mulberry, Senior Manager, Public Affairs, IEEE Standards Association, moderated the panel.

The IEEE volunteer-led panel discussed what standards developers and users are doing today to address sustainability and climate change. Panelists provided details on how to go beyond traditional approaches and sustainability targets to provide a wider cultural foundation for guiding the care of the planet, including technological innovations and the application of ethical design principles based on IEEE standards and best practices.

The panel also covered breakthroughs in collaboration, collective action, communication, governance, gaps, and business model reforms that are needed to be aligned with technologically sound solutions and innovations that can be adopted and practically deployed, which include approaches underway at the Oceanic Engineering Society to better understand and manage the ocean in order to sustainably benefit from its ecosystem and economic services.

This year’s IEEE Knowledge Café theme was “Beyond Strong Sustainability: Catalyzing a Planet Positive Future for Generations to Come” and was an opportunity to showcase the progress of IEEE SA’s Planet Positive 2030 initiative. Maike Luiken opened the interactive session by welcoming Tomas Lamanauskas, Deputy Secretary General of the ITU.

During this interactive session, IEEE volunteers acted as table facilitators, setting the stage for discussion and selecting topics based on charters from the IEEE SA Planet Positive work, including Accountability, Oceans, Smart Cities, and Policy. The background of each subject was presented and tables shared lively discussions on what they saw as the biggest sustainability gaps for that topic and suggestions for how to address them.

High-Level Policy sessions gathered high-ranking officials within the WSIS stakeholder community, representing government, private sector, civil society, academia, and international organizations. High-Level Track Facilitators (HLTFs) moderated the interactive policy statement sessions. They captured the vision, emerging trends, opportunities, and challenges governments face as they implement sustainable development goals.

During High-Level Policy Session 2: Enabling Environment, Thomas Coughlin spoke about how standards are essential in achieving sustainability. He noted that standards provide the critical framework for advancing sustainable technology, prioritizing people, the planet, and purpose-driven progress. They play an essential role in providing the procedures, guidelines, and specifications by which goods and services are produced, used, discarded, and recycled. This is an integral part of IEEE’s mission to advance technology for the benefit of humanity, and many diverse individuals and communities of IEEE around the world are using their expertise and know-how to help develop solutions for the critical sustainability issues the planet faces today. Rewatch the session here.

Maike Luiken was a panel member for the discussion on “Digital Cooperation and Partnerships for Inclusive Sustainable Development.” She noted that as we step closer to 2030, navigating the complexities of pursuing the UN SDGs needs to consider the diversity in culture, local, regional and global conditions and needs, and the varying contexts around the globe. It also requires flexibility and practical guidance on decisions and the implementation of these decisions by individuals, communities, companies, organizations, and governments.

She emphasized that the technical work that IEEE members do is increasingly expanding to new areas of technology and beyond technical solutions to addressing sustainable development and being inclusive of ethical and human values. The ongoing development of these powerful technologies and disruptive innovations in ICT demands a keener focus on social responsibility and accountability from the global technology community.

For example, IEEE focuses on best practices and standards for addressing sustainability, environmental stewardship, and climate change challenges through a pragmatic lens–such as standard P7800™ for Addressing Sustainability, Environmental Stewardship and Climate Change Challenges in Professional Practice, and IEEE P7010.1™ on Environmental Social Governance (ESG) and Social Development Goal (SDG) Action Implementation and Advancing Corporate Social Responsibility.

She remarked that IEEE, working in partnership with many other organizations, government and intergovernmental bodies, industry, academia, and more, has developed an ecosystem of programs and initiatives. The output of that work is best practices, standards, and certification programs that are open globally for partners to use in their efforts to help advance the 2030 Sustainable Development Agenda.

IEEE had the honor of having two representatives chosen to be High-Level Policy Track Facilitators and lead panel discussions of ministers and government officials during the two-day ministerial event that was held during WSIS week.

Antonio Luque, University of Seville, Spain (Region 8) led Session 6: Digital Economy and Trade/Financing for ICT.

The session discussed the opportunities that new digital economies present for development through public-private partnerships, research and development, and education and the initiatives the participants take to overcome the barriers to digital trade.

Antonio noted, “Bridging the digital divide is essential to fully exploit the benefits that digital trade can bring to everyone. Access, availability, and affordability should be the driving forces of digitalization.”

The near future will see increased confidence and trust in digital businesses if we are able to solve the challenges and provide equal access to connectivity and services. Bridging the digital divide is key for this, and the opportunities that will open are worth the effort.”

Karen Mulberry led Session 3: Building Confidence and Security in the Use of ICTs.

Ministers and panelists discussed the ongoing challenge of security, risks, and impacts of cyber threats and the need to protect and maintain trust in digital platforms and information. As more information, services, and knowledge are online, access to a safe environment is important for all to build a better ICT environment.

The IEEE @ WSIS Forum 2023 Delegation had many opportunities to exchange valuable experiences and insights on how standards development and the work of IEEE supports the UN’s Sustainable Development Goals.

To learn more about WSIS Forum 2023, view the event’s highlights and outcomes or watch on-demand participation videos to learn more about IEEE’s efforts to contribute to sustainable development at WSIS Forum 2023.

In the retail industry, manufacturers are accelerating the growth of their direct-to-consumer businesses; retailers are maturing private brand programs; and consumers expect personalized products and experiences as well as full transparency to responsible sourcing and sustainable practices. COVID-19 has also exposed the risks of traditional product creation models and long product development cycles.

Now in its fifth year, the 2022 3DRC Grand Challenge: 3D Virtualization for Retailers and Brands invited the academic and research communities to present creative research and solutions with the potential to transform how companies create, make, and sell new products by harnessing the power of digital product creation.

This year’s entries were tasked with developing people, process, and tech-related solutions that addressed the ability to scale and automate 3D product virtualization within any product lifecycle stage.

Based on applicability and the impact on business, technology, and society, Emersya was named by the 3D Retail Coalition Steering Committee as the 2022 Grand Challenge winner.

Emersya has been pioneering interactive 3D and augmented reality (AR) for digital product experiences for the past ten years. They developed an all-in-one online platform that empowers brands, manufacturers, and retailers to scale and automate 3D product virtualization across all stages of the create, make, and sell lifecycle. 

Manage 3D Assets 

Emersya’s agnostic platform allows brands to publish and optimize their 3D assets from any software, to visualize, enrich, and share them online easily. The platform breaks down the silos between different departments (design, development, marketing, sales, etc.) by providing an accessible, easy-to-use tool that enables everyone to work together. 

Create Variants 

Emersya provides brands with an easy-to-use online tool for creating new product variants by trying out different colors, materials, artwork, and graphics in real-time 3D. Designers can instantly create unlimited true-to-life virtual samples for their new product collection.

Share, Review, and Iterate 

Instead of in-person meetings with physical models, brand teams can review and discuss product designs online in interactive 3D and AR. This can cut the production of physical samples by 90% and reduce lead time by up to 50%, lowering overall costs and the environmental impact. 

Generate Tech Packs 

Once the colorway designs have been validated, Emersya can automatically generate Tech Packs, including the Bill of Materials and other data the brand requires for material sourcing and production. This data can be fed directly into the brand’s PLM to speed up the process, eliminate the error margin, and allow designers to spend more time on creative tasks. 

Automate Photo Shoots 

Emersya offers a virtual product photography solution that enables marketers to generate infinite numbers of true-to-life product images based on the 3D models of their products. This supports brands in creating more product visuals more efficiently—for all product colorways—ahead of time and at a lower cost.

Share and Embed 3D and AR Product Experiences 

For every product design created on the platform, Emersya automatically generates a link to visualize and share the design online, embed on a website, or use in B2B sales. Using the same assets, the platform also empowers brands to create web-based 3D easily and AR product experiences for B2C sales, online and in-store. These experiences drive consumer engagement, increase conversion rates, and build consumer loyalty, all while limiting product returns.

Made-to-Order and Customization

The Emersya platform provides brands with an easy, automatable process for setting up customizable or configurable products in 3D. From personalizing a product with engraving, embroidery, or imagery to creating a bespoke product, Emersya facilitates manufacturing custom products at scale by supplying production files and offering an online order management system. Offering made-to-order products helps companies produce more sustainably while reducing returns.

About 3D Virtualization for Retailers and Brands at IEEE SA

The 3DRC Grand Challenge is a joint initiative of the 3D Retail Coalition (3DRC), IEEE SA, and PI Apparel for the retail/apparel industry to explore technology applications and standards enabling next-generation consumer experiences. The project originated with support from the IEEE 3D Body Processing (3DBP) Industry Connections (IC) activity, a collaborative effort to assess standards opportunities intersecting emerging technologies to enhance industries such as retail, medical, health and wellness, and sports and athletics. Participation in 3DBP subgroups and activities is welcomed.

Learn more about the 3DRC Grand Challenge and the 3D Body Processing IC Activity.

In recent years, the global pandemic, extreme weather changes, conflicts, and inflation have contributed to a constrained and more expensive food market. A visit to the grocery store confirms that higher prices exist for most items. Clearly, we need to make agriculture supply chains more resilient to extreme events at every stage—from production to distribution. From the farm to the food market, new and emerging technologies are helping farmers grow more and better crops and optimize the complex agriculture supply chain.

Harvesting a good crop is never a sure thing. Despite efforts to follow best practices, farmers have faced difficult, unexpected, and uncontrollable circumstances, including pest infestations, plant diseases, and weather-related events such as droughts and floods. For some farmers, mostly large-scale operators in more developed countries, new technologies are helping predict, prepare, and adapt to these challenges. 

Among the technological advancements in the agriculture sector, the adoption of IoT sensors and integrated data platforms is accelerating. Just like the smart devices that enable us to monitor our health every minute of the day, agricultural sensors allow farmers to monitor conditions—weather, water supply levels, soil conditions, and more in basically real time. Data-informed insights can then be shared with regional stakeholders including other farmers, agricultural extension service officials, utility providers, and food distributors. In tandem, shared data from other sources, like the local water authority, can provide important inputs such as water availability.

As with all new technologies, there are some challenges. Unfortunately, many farmers, especially small-scale operators and those in remote regions, do not have the means to outfit their acreages with sensors due to many factors, including costs, lack of internet access, and feasibility of the technology. They cannot rely on data from nearby farmers to let them know a regional pest problem is hindering crop growth or receive predictive alerts that water supply will be at an all-time low due to severe drought. For an individual farmer, digital data can bring value, but the depth and quality of data are much stronger when it comes from multiple inputs, includes actionable insights, and is easily shared with all farmers, large and small. The rural connectivity challenges alone are compelling reasons why we must continue our efforts to increase wireless connectivity in rural areas.

Despite all of the challenges associated with costs and connectivity, in some regions all farmers can benefit from democratized data from these sensors. Farmers who may not be able to afford sensors or do not want to incorporate them in their own farms could have access to the data and could use this information for their own benefit, as well as research and development purposes. With smart agriculture data sets, farmers gain a better understanding of their acreage and potential yields.

Understanding and managing the supply chain—from production to silos to global customers—is a tremendously difficult challenge when factoring in the complexities of operational factors, such as unpredictable yields, and external factors, like drought, pricing volatility, and global imbalances in supply and demand. Data inputs from a region can provide predictability insights, including warning of a low-yield crop situation or a health alert for a diseased crop like E. coli, from a specific water source to food producers and distributors. 

As an example, smart technologies, IoT sensors, and blockchain can be leveraged to help farmers and distributors optimize storage conditions to help fight pest infestations, reduce spoilage, and fit more output into silos and other storage units. The technology exists for an IoT sensor to determine a product’s origin and other information, stored on blockchain. IoT sensors are highly effective in the warehouse environment, warning of changes in temperature and other conditions and triggering alarms when conditions are compromised. The chain of data is also invaluable to quickly trace the origins and factors involved with spoiled or adversely affected products, such as an outbreak of Salmonella in a small or large region.

Digital and analytics technologies can be used to run virtual simulations, allowing food distributors to optimize the best means to source supply and fulfill needs. Data inputs and simulation models can help government, healthcare, and food-related industries to better plan and adjust to crop shortages and surpluses and all issues related to their growth, harvest, and safe distribution. 

However, issues with data interoperability and sharing exist but can be addressed through the development of standards developed through industry consensus. As the trend of democratized data continues throughout the agriculture industry, we need to educate producers and other downstream stakeholders on the impact sensors and other technologies can have on farms and the overall integrity of the food supply chain. We need to continue to strive toward developing technologies that can be accessible and feasible for smaller producers who are a significant food source for the world’s food supply. Simply providing an IoT sensor to a farmer with some form of connectivity does not solve the problem. The key is for these tools to be practical, and an ability to utilize the data, and integrate and interoperate with the overall ecosystem.

IEEE SA is addressing these needs in many ways, including the formation of an Enabling a Smart and Equitable Agriculture Ecosystem Program, which is leveraging technologies such as  blockchain-based supply chain management solutions, Al-based digital agronomy, autonomous and semi autonomous machines, and loT/remote sensing solutions. The goal of this group is to understand the current state of open digital agronomy and  data interoperability, and recommend best practices and develop frameworks  for increasing collaboration around ag data collection, sharing, security, and management. Within these collaborations, multidisciplinary volunteers will propose standards and certification processes for data providers and consumers to accelerate innovation.