Smart Xchange
Overview
A thought leadership service design collaboration between EY Seren and the Royal College of Art that explores the relationship between people's trust in AI during moments of high emotion.
Categories
SaaS
AI-integrated services
Date
Feb 10, 2025
Client
EY Seren, RCA
In highly regulated sectors like finance, healthcare, and government, where trust and empathy are critical, how can AI provide human-centred support while maintaining efficiency? This project explores AI-driven solutions to bridge the empathy gap, ensuring effective and supportive customer interactions.
To address the challenge, we focused on four key areas: the moments that shape financial decisions, the emotions tied to those decisions, how behaviours and responses unfold in these interactions, and the role of trust and empathy in technology. These pillars guided our exploration into this project, focused on thought leadership.
Team In-Picture (from Left to Right): David Soh (me), Chen Bowen, Madeleine Mai, Sanyogita Nikam, Wang Liboyang, Devika Malik)
When relocating abroad, young women often grapple with the challenge of frequently exchanging money to achieve their desired lifestyle. With a limited budget and most finances held in their home currency, maximising the value received during currency exchanges becomes crucial, particularly when large expenses like rent or school fees are involved.
Smart Xchange is the culmination of four months of extensive design research, development, collaborative workshops, and user testing. This process allowed us to establish and confirm a reliable system that fosters user trust in AI, alleviating the stresses and routine tasks associated with relocating abroad.
Process
We first conducted a series of interviews with around 20 Young Women aged 25-30 to better understand their relationship with their finances. We gathered and drew key insights, utilising the "5 Whys" methodology to peel back the layers in understanding the needs of our targeted user group.
By analysing use cases, personas, and user journeys, we gained a deeper understanding of the challenges involved in relocating abroad. While we identified "budgeting" and "adapting to a new cultural context" as the main issues, we sought to employ tools like various forms of Root-Cause Analysis to explore why these challenges exist in greater detail.
We noted that the need for money plays a key role in fulfilling individuals' social, functional, and emotional needs in every use case. This leads to a desire to optimise their financial situation while still addressing those needs.
Our interviews found that women often harbour an idealised vision of their dream life in a different country. This wish fosters a yearning to live that ideal life abroad, often overlooking the practical responsibilities required to sustain it, like paying rent and utility bills and adjusting to a new cost of living.
We identified that during this journey, there is a moment of high emotion which is caused by a culmination of various moments of stress.
We termed it as a moment of "Compounded High Emotion(s)".
On this basis, we meticulously examined various small moments of emotion in that narrowed user journey, ultimately recognising the Uncontrollable Exchange Rate as a crucial factor in determining the key relationship an individual moving abroad has with their finances.
Our use case (above) was inspired by a few international postgraduate women we interviewed:
To better understand "Compounded High Emotions", imagine a large sum payment (such as a six-month rent payment) that requires an exchange of money in a week, coupled with school assignments due in two days, utility bills due in five days, and a friend’s birthday party due in six days.
Amidst an ever-changing foreign exchange market, picture the stress of seeking a favourable exchange rate, aware that it could save you hundreds of dollars, all while managing daily challenges.
Based on the relationship between the user and our problem, we identified a gap highlighting the potential for leveraging AI as an optimal solution to enable users to understand and mitigate the impacts of volatile exchange rates. By implementing a suite of analytical and automated AI-driven systems and functions, our objective is to empower users to maximise the value of their home currency effectively. (see map above)
Leading to our Problem statement:
"Young women moving abroad struggle to make confident financial decisions during currency exchange because they face unpredictable market conditions and lack familiarity with the financial system. Therefore, they often experience emotional stress and risk running out of funds during critical moments of their transition."
Thus, leveraging insights from our secondary research, alongside the challenges and opportunities uncovered in our primary research, we formulated a targeted "How Might We" statement, which also served as a foundation for generating several hypotheses we explored, ideated and tested.
Prototyping and Testing
To test, we conducted a series of prototyping and co-design workshops to test the features built from the four hypotheses, as seen above. We hypothesise that an AI-powered platform integrating various features can help young women overseas manage currency exchanges efficiently, minimising emotional stress and financial risk.
We embarked on our testing journey by using one platform as a standalone option, while integrating two others into a trusted framework. Our goal was to explore how much users would embrace this intervention. While we primarily focused on women, including both genders allowed us to discover valuable insights about trust in technology across different perspectives.
We systematically aligned each hypothesis with an AI-driven feature intended for evaluation in our workshop. Our primary focus was to analyse real-time AI insights regarding market rates, specifically investigating whether alerts concerning financial risks or losses prompted users to take proactive measures in response to currency volatility.
For personalised financial notifications, we assessed the impact of notification frequency on user engagement and platform utilisation.
Lastly, in the area of empathetic nudges, we examined how AI-generated content and contextually tailored language enhanced engagement levels among our target demographic of young women.
Validation of Hypotheses
From our workshops, we uncovered some illuminating insights:
Social validation emerged as a key theme; women actively sought out reliable, often human, sources for guidance before making any decisions.
Personalisation truly resonated with women, significantly enhancing their trust in the intervention.
Automation proved to be a game-changer, relieving the burden of daily tasks that often feel overwhelming in a busy life.
Finally, the question of accountability surfaced—who can users rely on if things don't go as planned?
Our workshop helped validate several aspects of our hypotheses. The strongest support was for personalised financial alerts based on individual goals.
As one participant shared,
'It would be great if it knew how much I spent each month and told me how much to transfer based on my targeted rate."
However, for real-time AI market insights, many participants expressed a preference for turning to Google or other trusted sources instead. Lastly, when it came to notifications, participants favoured subtle language that prompted action, combined with relevant content."
Key Insights:
Through multiple sessions of testing and feedback, we found that our female users/participants derive trust from three key principles that we developed into a Pyramid:
Accountability, the core foundation, as individuals seek clarity on who is responsible for information and who can be held accountable when issues arise.
User Agency, reflecting the desire for individuals to maintain control over their financial decisions.
Empathetic Language, demonstrating that young women respond positively to communication that is supportive, uplifting, and informative.
In response to these findings, our intervention was designed to incorporate features that specifically address these trust-building elements, with the goal of fostering and gradually enhancing user trust over time.
To solidify our intervention's concept, we utilised the "Jobs to Be Done" framework to clearly define the intentions and consequences linked to our feature’s implementation.
When young international female graduates move abroad to chase their dreams, our ideal outcome is to enhance their ability to make informed financial choices, reduce monetary losses, and eliminate the tedious task of constantly tracking fluctuating exchange rates.
Final Concept: Smart Xchange
By synthesising findings through prototyping, our final concept was Smart Xchange, automated currency management made easy. Transitioning from routine, manual oversight to streamlined automated control that is integrated into a pre-established, reliable platform.
The key features of this concept are as follow:
Feature 1: Controlled Automations
This feature empowers users to define a target exchange rate and receive instant AI notifications once that rate is achieved. Additionally, users can automate transactions, allowing them to capitalise on favourable market conditions without manual intervention.
By setting the desired exchange rate, and the AI will notify you when it’s met — or even execute the transaction automatically on the user’s behalf, ensuring they never miss out on optimal exchange rates.
Ultimately, this feature enhances user control over their financial transfers, streamlining the process for a more efficient and effective experience.
Feature 2: Smart Predictions
Prediction Analysis paired with Consumption Analysis empowers user agency by integrating advanced predictive analytics with in-depth consumption analysis, driving a higher level of personalisation and fostering user trust.
The predictive AI systematically examines users’ consumption patterns alongside fluctuating exchange rate trends to provide tailored recommendations on optimal exchange timings. This approach not only enhances decision-making but also strengthens the service experience by aligning with users’ financial behaviours and expectations.
Feature 3: Empathetic Nudges and Alerts
During our workshop, participants indicated a preference for notifications that are communicative and approachable, encouraging proactive engagement.
Thus, our final key feature is Personalised and Empathetic Alerts, where users will obtain insights specifically designed around their spending behaviours and financial objectives, articulated in a warm and friendly tone suitable for fostering connection and understanding.
Conclusion
To build trust in AI, particularly among young women, it's essential to communicate effectively.
Consider designing services that fulfil three essential roles: addressing functional, emotional, and social needs. By rigorously integrating these into the design process, we can ensure that our services resonate meaningfully with the target audience and produce a significant positive impact during moments of high emotion.
Finally, I would like to draw back to our Pyramid for Trust when designing an AI-Driven service:
Accountability: Design processes must emphasise transparency and responsibility to gain user trust.
User Agency: Empower users by providing them with choices and control (or the illusion thereof) over their interactions with AI services.
Empathetic Language: Use language that resonates with users on an emotional level, fostering a sense of connection and understanding.
In conclusion, embedding these core principles in your design will not only enhance user experience but also build a strong foundation for trust in AI among young women.
Smart Xchange
Overview
A thought leadership service design collaboration between EY Seren and the Royal College of Art that explores the relationship between people's trust in AI during moments of high emotion.
Categories
SaaS
AI-integrated services
Date
Feb 10, 2025
Client
EY Seren, RCA
In highly regulated sectors like finance, healthcare, and government, where trust and empathy are critical, how can AI provide human-centred support while maintaining efficiency? This project explores AI-driven solutions to bridge the empathy gap, ensuring effective and supportive customer interactions.
To address the challenge, we focused on four key areas: the moments that shape financial decisions, the emotions tied to those decisions, how behaviours and responses unfold in these interactions, and the role of trust and empathy in technology. These pillars guided our exploration into this project, focused on thought leadership.
Team In-Picture (from Left to Right): David Soh (me), Chen Bowen, Madeleine Mai, Sanyogita Nikam, Wang Liboyang, Devika Malik)
When relocating abroad, young women often grapple with the challenge of frequently exchanging money to achieve their desired lifestyle. With a limited budget and most finances held in their home currency, maximising the value received during currency exchanges becomes crucial, particularly when large expenses like rent or school fees are involved.
Smart Xchange is the culmination of four months of extensive design research, development, collaborative workshops, and user testing. This process allowed us to establish and confirm a reliable system that fosters user trust in AI, alleviating the stresses and routine tasks associated with relocating abroad.
Process
We first conducted a series of interviews with around 20 Young Women aged 25-30 to better understand their relationship with their finances. We gathered and drew key insights, utilising the "5 Whys" methodology to peel back the layers in understanding the needs of our targeted user group.
By analysing use cases, personas, and user journeys, we gained a deeper understanding of the challenges involved in relocating abroad. While we identified "budgeting" and "adapting to a new cultural context" as the main issues, we sought to employ tools like various forms of Root-Cause Analysis to explore why these challenges exist in greater detail.
We noted that the need for money plays a key role in fulfilling individuals' social, functional, and emotional needs in every use case. This leads to a desire to optimise their financial situation while still addressing those needs.
Our interviews found that women often harbour an idealised vision of their dream life in a different country. This wish fosters a yearning to live that ideal life abroad, often overlooking the practical responsibilities required to sustain it, like paying rent and utility bills and adjusting to a new cost of living.
We identified that during this journey, there is a moment of high emotion which is caused by a culmination of various moments of stress.
We termed it as a moment of "Compounded High Emotion(s)".
On this basis, we meticulously examined various small moments of emotion in that narrowed user journey, ultimately recognising the Uncontrollable Exchange Rate as a crucial factor in determining the key relationship an individual moving abroad has with their finances.
Our use case (above) was inspired by a few international postgraduate women we interviewed:
To better understand "Compounded High Emotions", imagine a large sum payment (such as a six-month rent payment) that requires an exchange of money in a week, coupled with school assignments due in two days, utility bills due in five days, and a friend’s birthday party due in six days.
Amidst an ever-changing foreign exchange market, picture the stress of seeking a favourable exchange rate, aware that it could save you hundreds of dollars, all while managing daily challenges.
Based on the relationship between the user and our problem, we identified a gap highlighting the potential for leveraging AI as an optimal solution to enable users to understand and mitigate the impacts of volatile exchange rates. By implementing a suite of analytical and automated AI-driven systems and functions, our objective is to empower users to maximise the value of their home currency effectively. (see map above)
Leading to our Problem statement:
"Young women moving abroad struggle to make confident financial decisions during currency exchange because they face unpredictable market conditions and lack familiarity with the financial system. Therefore, they often experience emotional stress and risk running out of funds during critical moments of their transition."
Thus, leveraging insights from our secondary research, alongside the challenges and opportunities uncovered in our primary research, we formulated a targeted "How Might We" statement, which also served as a foundation for generating several hypotheses we explored, ideated and tested.
Prototyping and Testing
To test, we conducted a series of prototyping and co-design workshops to test the features built from the four hypotheses, as seen above. We hypothesise that an AI-powered platform integrating various features can help young women overseas manage currency exchanges efficiently, minimising emotional stress and financial risk.
We embarked on our testing journey by using one platform as a standalone option, while integrating two others into a trusted framework. Our goal was to explore how much users would embrace this intervention. While we primarily focused on women, including both genders allowed us to discover valuable insights about trust in technology across different perspectives.
We systematically aligned each hypothesis with an AI-driven feature intended for evaluation in our workshop. Our primary focus was to analyse real-time AI insights regarding market rates, specifically investigating whether alerts concerning financial risks or losses prompted users to take proactive measures in response to currency volatility.
For personalised financial notifications, we assessed the impact of notification frequency on user engagement and platform utilisation.
Lastly, in the area of empathetic nudges, we examined how AI-generated content and contextually tailored language enhanced engagement levels among our target demographic of young women.
Validation of Hypotheses
From our workshops, we uncovered some illuminating insights:
Social validation emerged as a key theme; women actively sought out reliable, often human, sources for guidance before making any decisions.
Personalisation truly resonated with women, significantly enhancing their trust in the intervention.
Automation proved to be a game-changer, relieving the burden of daily tasks that often feel overwhelming in a busy life.
Finally, the question of accountability surfaced—who can users rely on if things don't go as planned?
Our workshop helped validate several aspects of our hypotheses. The strongest support was for personalised financial alerts based on individual goals.
As one participant shared,
'It would be great if it knew how much I spent each month and told me how much to transfer based on my targeted rate."
However, for real-time AI market insights, many participants expressed a preference for turning to Google or other trusted sources instead. Lastly, when it came to notifications, participants favoured subtle language that prompted action, combined with relevant content."
Key Insights:
Through multiple sessions of testing and feedback, we found that our female users/participants derive trust from three key principles that we developed into a Pyramid:
Accountability, the core foundation, as individuals seek clarity on who is responsible for information and who can be held accountable when issues arise.
User Agency, reflecting the desire for individuals to maintain control over their financial decisions.
Empathetic Language, demonstrating that young women respond positively to communication that is supportive, uplifting, and informative.
In response to these findings, our intervention was designed to incorporate features that specifically address these trust-building elements, with the goal of fostering and gradually enhancing user trust over time.
To solidify our intervention's concept, we utilised the "Jobs to Be Done" framework to clearly define the intentions and consequences linked to our feature’s implementation.
When young international female graduates move abroad to chase their dreams, our ideal outcome is to enhance their ability to make informed financial choices, reduce monetary losses, and eliminate the tedious task of constantly tracking fluctuating exchange rates.
Final Concept: Smart Xchange
By synthesising findings through prototyping, our final concept was Smart Xchange, automated currency management made easy. Transitioning from routine, manual oversight to streamlined automated control that is integrated into a pre-established, reliable platform.
The key features of this concept are as follow:
Feature 1: Controlled Automations
This feature empowers users to define a target exchange rate and receive instant AI notifications once that rate is achieved. Additionally, users can automate transactions, allowing them to capitalise on favourable market conditions without manual intervention.
By setting the desired exchange rate, and the AI will notify you when it’s met — or even execute the transaction automatically on the user’s behalf, ensuring they never miss out on optimal exchange rates.
Ultimately, this feature enhances user control over their financial transfers, streamlining the process for a more efficient and effective experience.
Feature 2: Smart Predictions
Prediction Analysis paired with Consumption Analysis empowers user agency by integrating advanced predictive analytics with in-depth consumption analysis, driving a higher level of personalisation and fostering user trust.
The predictive AI systematically examines users’ consumption patterns alongside fluctuating exchange rate trends to provide tailored recommendations on optimal exchange timings. This approach not only enhances decision-making but also strengthens the service experience by aligning with users’ financial behaviours and expectations.
Feature 3: Empathetic Nudges and Alerts
During our workshop, participants indicated a preference for notifications that are communicative and approachable, encouraging proactive engagement.
Thus, our final key feature is Personalised and Empathetic Alerts, where users will obtain insights specifically designed around their spending behaviours and financial objectives, articulated in a warm and friendly tone suitable for fostering connection and understanding.
Conclusion
To build trust in AI, particularly among young women, it's essential to communicate effectively.
Consider designing services that fulfil three essential roles: addressing functional, emotional, and social needs. By rigorously integrating these into the design process, we can ensure that our services resonate meaningfully with the target audience and produce a significant positive impact during moments of high emotion.
Finally, I would like to draw back to our Pyramid for Trust when designing an AI-Driven service:
Accountability: Design processes must emphasise transparency and responsibility to gain user trust.
User Agency: Empower users by providing them with choices and control (or the illusion thereof) over their interactions with AI services.
Empathetic Language: Use language that resonates with users on an emotional level, fostering a sense of connection and understanding.
In conclusion, embedding these core principles in your design will not only enhance user experience but also build a strong foundation for trust in AI among young women.
Smart Xchange
Overview
A thought leadership service design collaboration between EY Seren and the Royal College of Art that explores the relationship between people's trust in AI during moments of high emotion.
Categories
SaaS
AI-integrated services
Date
Feb 10, 2025
Client
EY Seren, RCA
In highly regulated sectors like finance, healthcare, and government, where trust and empathy are critical, how can AI provide human-centred support while maintaining efficiency? This project explores AI-driven solutions to bridge the empathy gap, ensuring effective and supportive customer interactions.
To address the challenge, we focused on four key areas: the moments that shape financial decisions, the emotions tied to those decisions, how behaviours and responses unfold in these interactions, and the role of trust and empathy in technology. These pillars guided our exploration into this project, focused on thought leadership.
Team In-Picture (from Left to Right): David Soh (me), Chen Bowen, Madeleine Mai, Sanyogita Nikam, Wang Liboyang, Devika Malik)
When relocating abroad, young women often grapple with the challenge of frequently exchanging money to achieve their desired lifestyle. With a limited budget and most finances held in their home currency, maximising the value received during currency exchanges becomes crucial, particularly when large expenses like rent or school fees are involved.
Smart Xchange is the culmination of four months of extensive design research, development, collaborative workshops, and user testing. This process allowed us to establish and confirm a reliable system that fosters user trust in AI, alleviating the stresses and routine tasks associated with relocating abroad.
Process
We first conducted a series of interviews with around 20 Young Women aged 25-30 to better understand their relationship with their finances. We gathered and drew key insights, utilising the "5 Whys" methodology to peel back the layers in understanding the needs of our targeted user group.
By analysing use cases, personas, and user journeys, we gained a deeper understanding of the challenges involved in relocating abroad. While we identified "budgeting" and "adapting to a new cultural context" as the main issues, we sought to employ tools like various forms of Root-Cause Analysis to explore why these challenges exist in greater detail.
We noted that the need for money plays a key role in fulfilling individuals' social, functional, and emotional needs in every use case. This leads to a desire to optimise their financial situation while still addressing those needs.
Our interviews found that women often harbour an idealised vision of their dream life in a different country. This wish fosters a yearning to live that ideal life abroad, often overlooking the practical responsibilities required to sustain it, like paying rent and utility bills and adjusting to a new cost of living.
We identified that during this journey, there is a moment of high emotion which is caused by a culmination of various moments of stress.
We termed it as a moment of "Compounded High Emotion(s)".
On this basis, we meticulously examined various small moments of emotion in that narrowed user journey, ultimately recognising the Uncontrollable Exchange Rate as a crucial factor in determining the key relationship an individual moving abroad has with their finances.
Our use case (above) was inspired by a few international postgraduate women we interviewed:
To better understand "Compounded High Emotions", imagine a large sum payment (such as a six-month rent payment) that requires an exchange of money in a week, coupled with school assignments due in two days, utility bills due in five days, and a friend’s birthday party due in six days.
Amidst an ever-changing foreign exchange market, picture the stress of seeking a favourable exchange rate, aware that it could save you hundreds of dollars, all while managing daily challenges.
Based on the relationship between the user and our problem, we identified a gap highlighting the potential for leveraging AI as an optimal solution to enable users to understand and mitigate the impacts of volatile exchange rates. By implementing a suite of analytical and automated AI-driven systems and functions, our objective is to empower users to maximise the value of their home currency effectively. (see map above)
Leading to our Problem statement:
"Young women moving abroad struggle to make confident financial decisions during currency exchange because they face unpredictable market conditions and lack familiarity with the financial system. Therefore, they often experience emotional stress and risk running out of funds during critical moments of their transition."
Thus, leveraging insights from our secondary research, alongside the challenges and opportunities uncovered in our primary research, we formulated a targeted "How Might We" statement, which also served as a foundation for generating several hypotheses we explored, ideated and tested.
Prototyping and Testing
To test, we conducted a series of prototyping and co-design workshops to test the features built from the four hypotheses, as seen above. We hypothesise that an AI-powered platform integrating various features can help young women overseas manage currency exchanges efficiently, minimising emotional stress and financial risk.
We embarked on our testing journey by using one platform as a standalone option, while integrating two others into a trusted framework. Our goal was to explore how much users would embrace this intervention. While we primarily focused on women, including both genders allowed us to discover valuable insights about trust in technology across different perspectives.
We systematically aligned each hypothesis with an AI-driven feature intended for evaluation in our workshop. Our primary focus was to analyse real-time AI insights regarding market rates, specifically investigating whether alerts concerning financial risks or losses prompted users to take proactive measures in response to currency volatility.
For personalised financial notifications, we assessed the impact of notification frequency on user engagement and platform utilisation.
Lastly, in the area of empathetic nudges, we examined how AI-generated content and contextually tailored language enhanced engagement levels among our target demographic of young women.
Validation of Hypotheses
From our workshops, we uncovered some illuminating insights:
Social validation emerged as a key theme; women actively sought out reliable, often human, sources for guidance before making any decisions.
Personalisation truly resonated with women, significantly enhancing their trust in the intervention.
Automation proved to be a game-changer, relieving the burden of daily tasks that often feel overwhelming in a busy life.
Finally, the question of accountability surfaced—who can users rely on if things don't go as planned?
Our workshop helped validate several aspects of our hypotheses. The strongest support was for personalised financial alerts based on individual goals.
As one participant shared,
'It would be great if it knew how much I spent each month and told me how much to transfer based on my targeted rate."
However, for real-time AI market insights, many participants expressed a preference for turning to Google or other trusted sources instead. Lastly, when it came to notifications, participants favoured subtle language that prompted action, combined with relevant content."
Key Insights:
Through multiple sessions of testing and feedback, we found that our female users/participants derive trust from three key principles that we developed into a Pyramid:
Accountability, the core foundation, as individuals seek clarity on who is responsible for information and who can be held accountable when issues arise.
User Agency, reflecting the desire for individuals to maintain control over their financial decisions.
Empathetic Language, demonstrating that young women respond positively to communication that is supportive, uplifting, and informative.
In response to these findings, our intervention was designed to incorporate features that specifically address these trust-building elements, with the goal of fostering and gradually enhancing user trust over time.
To solidify our intervention's concept, we utilised the "Jobs to Be Done" framework to clearly define the intentions and consequences linked to our feature’s implementation.
When young international female graduates move abroad to chase their dreams, our ideal outcome is to enhance their ability to make informed financial choices, reduce monetary losses, and eliminate the tedious task of constantly tracking fluctuating exchange rates.
Final Concept: Smart Xchange
By synthesising findings through prototyping, our final concept was Smart Xchange, automated currency management made easy. Transitioning from routine, manual oversight to streamlined automated control that is integrated into a pre-established, reliable platform.
The key features of this concept are as follow:
Feature 1: Controlled Automations
This feature empowers users to define a target exchange rate and receive instant AI notifications once that rate is achieved. Additionally, users can automate transactions, allowing them to capitalise on favourable market conditions without manual intervention.
By setting the desired exchange rate, and the AI will notify you when it’s met — or even execute the transaction automatically on the user’s behalf, ensuring they never miss out on optimal exchange rates.
Ultimately, this feature enhances user control over their financial transfers, streamlining the process for a more efficient and effective experience.
Feature 2: Smart Predictions
Prediction Analysis paired with Consumption Analysis empowers user agency by integrating advanced predictive analytics with in-depth consumption analysis, driving a higher level of personalisation and fostering user trust.
The predictive AI systematically examines users’ consumption patterns alongside fluctuating exchange rate trends to provide tailored recommendations on optimal exchange timings. This approach not only enhances decision-making but also strengthens the service experience by aligning with users’ financial behaviours and expectations.
Feature 3: Empathetic Nudges and Alerts
During our workshop, participants indicated a preference for notifications that are communicative and approachable, encouraging proactive engagement.
Thus, our final key feature is Personalised and Empathetic Alerts, where users will obtain insights specifically designed around their spending behaviours and financial objectives, articulated in a warm and friendly tone suitable for fostering connection and understanding.
Conclusion
To build trust in AI, particularly among young women, it's essential to communicate effectively.
Consider designing services that fulfil three essential roles: addressing functional, emotional, and social needs. By rigorously integrating these into the design process, we can ensure that our services resonate meaningfully with the target audience and produce a significant positive impact during moments of high emotion.
Finally, I would like to draw back to our Pyramid for Trust when designing an AI-Driven service:
Accountability: Design processes must emphasise transparency and responsibility to gain user trust.
User Agency: Empower users by providing them with choices and control (or the illusion thereof) over their interactions with AI services.
Empathetic Language: Use language that resonates with users on an emotional level, fostering a sense of connection and understanding.
In conclusion, embedding these core principles in your design will not only enhance user experience but also build a strong foundation for trust in AI among young women.
