{"id":98,"date":"2024-12-12T11:12:14","date_gmt":"2024-12-12T11:12:14","guid":{"rendered":"https:\/\/www.biworldwide.com\/en-in\/?p=98"},"modified":"2026-07-24T17:35:38","modified_gmt":"2026-07-24T12:05:38","slug":"the-human-side-of-ai-in-rr-insights-into-behavioral-science-psychology","status":"publish","type":"post","link":"https:\/\/www.biworldwide.com\/en-in\/our-work\/blog\/the-human-side-of-ai-in-rr-insights-into-behavioral-science-psychology\/","title":{"rendered":"The Human Side of AI in R&R: Insights into Behavioural Science & Psychology"},"content":{"rendered":"\n
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\n\t\t\t\tThe Human Side of AI in Employee R&R: Insights into Behavioural Science & Psychology\t\t\t<\/h1>\n\t\t\t\t\t\t\t\t\t\t
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In today’s tech-driven world, AI is transforming everyday experiences and business operations. As it evolves, understanding its psychological impact is key\u2014especially in AI-powered Employee Reward & Recognition (R&R) programs<\/a>. By applying behavioural science, organisations can design R&R strategies that truly engage and drive performance.<\/p>\n\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t<\/div>\n<\/div>\n\n\n\n

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In today\u2019s rapidly-evolving techn landscape, AI is emerging as an integral force shaping our everyday experiences and business operations. However, as AI solutions become increasingly sophisticated, they also begin to exhibit human-like characteristics, prompting critical questions about the psychology behind AI. Particularly, this is relevant for designing and implementing behavioural science-led Employee Reward and Recognition (R&R) programs<\/a> that rely on the power of AI-driven insights.<\/p>\n\n\n\n

A global leader and India\u2019s foremost in providing AI and behavioural science-led employee R&R and engagement solutions<\/a>, BI WORLDWIDE helps organisations design R&R strategies that create inspiring employee experiences, activate desired behaviours and drive business results that matter.  <\/p>\n\n\n\n

Here are the key focus areas to consider when conceptualising AI-powered R&R strategies: <\/h3>\n\n\n\n

Making Artificial Authentic: Embedding Human-Like Traits in AI<\/h2>\n\n\n\n

AI solutions must evolve continuously to effectively demonstrate human-like qualities. For instance, a nuanced understanding of human preferences and enhanced decision-making capabilities are critical to eliminate biases \u2013 a challenge even humans grapple to overcome. Moreover, AI must be engineered to mitigate the risks of errors stemming from flawed or insufficient data inputs, a phenomenon called \u2018hallucination.\u2019 Addressing these complexities is essential for fostering trust and reliability in AI-driven systems.<\/p>\n\n\n\n

From Bias to Balance: Making AI Recognition Models Fairer<\/strong><\/h2>\n\n\n\n

AI-driven recognition models are susceptible to various biases that must be eliminated to uphold fairness and precision. A proactive approach to identify, analyse and mitigate biases embedded in data, algorithms or decision-making processes is essential.<\/p>\n\n\n\n

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  1. Recency Effect<\/strong>: AI models should balance the influences of recent and past data to preserve human tendencies as well as analytical accuracy. For instance, a manager consistently appreciating specific behaviours may unintentionally create a pattern in recognitions. So, when this manager is trying to recognise a different behavior, AI should not fall trap to recency effect by generating repetitive or overly similar outputs. Instead, the system should provide nuanced and contextually appropriate responses, reflecting the unique nature of the new recognition.
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  2. Emotion-Specific Recognition Bias<\/strong>: AI models must align with an organisation\u2019s communication culture and interpret emotional cues (including facial expressions) to provide accurate, meaningful recognition recommendations. Leveraging advanced models like Affectiva’s emotion AI technology and Claude Sonnet LLM models can prove instrumental. The models are designed to identify emotional biases through training on diverse datasets, fostering equitable and inclusive interactions across varied cultural contexts.  
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  3. Inequality Bias<\/strong>: Algorithmic bias can lead to issues like \u2018data colonisation\u2019, where certain groups may remain underrepresented or marginalized. Regular auditing and continuous training are essential to prevent such biases and foster inclusivity. For instance, AI-led recruitment tools like HireVue leverage video interviews to evaluate candidates, yet actively mitigate bias through frequent algorithm audits and integration of varied training data. This is achieved by implementing Explainable AI (XAI) models, designed to make AI decisions more transparent to humans through clear, interpretable insights. Techniques like SHAP (SHapley Additive exPlanations) and LIME (Local Interpretable Model-Agnostic Explanations) are key in XAI, enabling understanding, documentation and audit of AI decisions, ensuring fairness and accountability across diverse candidate groups.
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  4. AI and Choice Architecture: <\/strong>AI-led choice architecture can transform managerial decisions, particularly for recognition and loyalty programs<\/a>. However, its implementation demands human oversight and real-time feedback loops, ensuring that the AI-led choices are valid and beneficial. Additionally, \u2018hypernudging\u2019 \u2013 where AI continuously adapts to the decision-maker\u2019s preferences \u2013 must be controlled to prevent biases and unintended outcomes.
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  5. Impact of AI in Alleviating Decision Fatigue: <\/strong>Decision fatigue occurs when individuals become mentally exhausted from making numerous decisions, leading to diminished decision quality. AI can mitigate decision fatigue by automating routine decisions and providing robust decision support for more intricate scenarios. For instance, AI can efficiently manage repetitive tasks like sending festival greetings or event invitations, reducing the cognitive load on decision-makers. However, for more nuanced tasks like recognising contributions in a challenging project or crafting a special motivational acknowledgment, AI can provide thoughtful, context-driven recommendations. Further personalisation of such recommendations can be realised with a human touch, depending on the recogniser\u2019s affinity with the recognisee, striking a balance between efficiency and human judgment.<\/li>\n<\/ol>\n\n\n\n

    Backed by data analytics for R&R programs<\/a>, these bias-mitigation practices give CHROs and HRs an auditable and defensible way to prove that AI-driven recognition is fair \u2013 not just fast. <\/p>\n\n\n\n

    Transforming Insights into Impact: Revolutionising Employee R&R with AI<\/h2>\n\n\n\n
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    1. Recognition Authoring:<\/strong> Advanced AI models like Claude and ChatGPT empower recognisers to craft thoughtful and meaningful messages with ease. By providing contextual suggestions and pre-structured templates, these tools ensure that recognitions<\/a> are personalised and impactful, reducing the effort needed to articulate sentiments while maintaining authenticity.
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    2. Performance and Productivity Incentives:<\/strong> AI can set clear performance goals and design exciting reward systems for driving excellence. By aligning recognition with quantifiable accomplishments, AI fosters a culture of accountability, inspiring employees to consistently exceed expectations. Pairing this with gamification to drive engagement<\/a> further reinforces the behaviours you want to see repeated.
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    3. Performance Amplifier:<\/strong> When an individual creates their performance record, AI can efficiently bring together all third-party recognitions received during the evaluation period. Often, individuals and managers focus on recent achievements, inadvertently overlooking earlier recognitions. By ensuring a holistic showcase of accomplishments, AI reinforces the full spectrum of contributions that merit acknowledgment.
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    4. Wellness Initiatives:<\/strong> AI-driven wellness programs enhance engagement in activities like step challenges and mental health campaigns by incentivising participation with rewards<\/a>. By integrating wellness into recognition programs, AI can cultivate a culture of wellbeing and positivity at the workplace, especially when combined with gamification that makes participation visible and fun. <\/li>\n<\/ol>\n\n\n\n

      AI that Speaks the Language of Appreciation: Personalising Gratitude with LLM Models<\/h2>\n\n\n\n
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      1. OpenAI\u2019s GPT-5<\/strong>: Renowned for its versatility, GPT-5 generates personalised recognition notes, analyses feedback and provides actionable insights to elevate employee engagement. It can also assist in crafting comprehensive performance reviews and impactful recognition announcements, tailored to individual contributions.
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      2. Anthropic\u2019s Claude:<\/strong> Designed with a strong focus on alignment with human values, Claude helps create fair and unbiased recognition programs. It analyses employee interactions, identifies patterns of positive behaviour and proactively recommends meaningful recognition opportunities, ensuring inclusivity and equity in workplace appreciation.
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      3. Google\u2019s Gemini: <\/strong>Rebranded from Bard to Gemini, the AI assistant excels at creating high-quality, engaging content for recognition initiatives \u2013 from newsletters and social media posts to internal communications. It also offers robust sentiment analysis capabilities, enabling organisations to monitor and improve employee morale, by identifying engagement trends over time.<\/li>\n<\/ol>\n\n\n\n

        Responsible AI in R&R: The New Foundation for Futuristic Workplace<\/h2>\n\n\n\n

        AI is making transformative waves in the employee rewards and recognition landscape. AI-led R&R programs empower organisations to cultivate an inclusive work culture, boost employee morale and drive productivity. However, the success of these programs relies on maintaining human oversight, ensuring ethical implementation and establishing robust audits to maintain transparency and accountability. By leveraging AI responsibly, organisations can design compelling R&R programs that not only celebrate achievements but also foster a work culture rooted in positivity, equity and inspiration.<\/p>\n\n\n\n

        For a deeper look at building that oversight into your organisation’s wider AI adoption roadmap,<\/a> explore our board-level AI governance framework. <\/p>\n\n\n\n

        Frequently Asked Questions<\/h2>\n\n\n\n
        How is an AI-powered recognition platform different from a generic AI chatbot used by HRs?<\/strong>\u00a0<\/strong>

        While\u00a0a generic AI\u00a0HR chatbot\u00a0answers\u00a0employee queries and automates\u00a0routine HR tasks, a\u00a0dedicated\u00a0AI-powered recognition platform\u00a0is designed to actively drive engagement. It\u00a0creates on-time,\u00a0personalised recognition\u00a0experiences\u00a0that reinforce\u00a0the\u00a0behaviours,\u00a0values and performance outcomes\u00a0that matter to your\u00a0business. This\u00a0is how\u00a0AI in employee rewards and recognition\u00a0programs\u00a0helps strengthen culture, elevate productivity, and\u00a0unlock\u00a0the ROI of R&R programs.\u00a0<\/p> <\/div>

        How do you measure the ROI of AI-powered recognition programs?\u00a0<\/strong>\u00a0<\/strong>

        The\u00a0ROI of employee recognition<\/a>\u00a0programs\u00a0is measured\u00a0by tangible\u00a0business outcomes\u00a0such as\u00a0engagement,\u00a0retention,\u00a0productivity\u00a0and\u00a0performance\u00a0\u2013\u00a0not\u00a0just\u00a0the number of recognitions sent or rewards redeemed.\u00a0AI-powered\u00a0R&R\u00a0platforms\u00a0make this easier by surfacing real-time, data-driven insights,\u00a0predictive analytics,\u00a0and actionable recommendations,\u00a0instead of retrospective reporting, turning\u00a0recognition into a\u00a0measurable\u00a0lever for\u00a0business\u00a0performance.\u00a0<\/p> <\/div>

        Do AI-powered\u00a0recognition\u00a0platforms\u00a0support regional languages, not just English?<\/strong><\/strong>

        Yes.\u00a0New-age AI-powered R&R platforms support multiple regional languages, making recognition more inclusive and meaningful.\u00a0Language is\u00a0often a key barrier\u00a0to\u00a0the adoption of AI-powered R&R programs,\u00a0especially\u00a0among\u00a0regional\u00a0and frontline\u00a0workforces.\u00a0In\u00a0countries like\u00a0India,\u00a0multilingual\u00a0support\u00a0ensures\u00a0recognition reaches every employee,\u00a0as\u00a0recognition delivered only in English can exclude\u00a0a significant portion\u00a0of the workforce it aims to engage.\u00a0This helps\u00a0organisations\u00a0drive engagement across the board and\u00a0maximise the\u00a0ROI of R&R\u00a0programs.\u00a0<\/p> <\/div>

        Can AI-powered recognition platforms\u00a0adapt to a multigenerational and multicultural workforce?\u00a0<\/strong>\u00a0<\/strong>

        Absolutely.\u00a0This is\u00a0often a big barrier for adopting\u00a0AI-powered\u00a0R&R platforms\u00a0in India.\u00a0However,\u00a0such\u00a0platforms\u00a0enable\u00a0personalising\u00a0recognition\u00a0for\u00a0generations,\u00a0roles,\u00a0cultural\u00a0nuances\u00a0and individual preferences\u00a0across a diverse workforce.\u00a0This ensures recognition feels authentic,\u00a0relevant\u00a0and motivating\u00a0for every employee, while helping organisations\u00a0unlock\u00a0the\u00a0ROI of\u00a0R&R\u00a0programs.\u00a0<\/p> <\/div>

        How do AI-powered recognition programs work for frontline, factory-floor and deskless employees?<\/strong>\u00a0<\/strong>

        AI-powered R&R platforms\u00a0are built to\u00a0enable recognition for\u00a0frontline, factory-floor and deskless employees\u00a0through mobile-first, easy-to-access\u00a0experiences that do\u00a0not rely on\u00a0desktop access.\u00a0The platforms\u00a0also\u00a0simplify rewards\u00a0redemption\u00a0for such employees,\u00a0helping organisations create a more inclusive\u00a0culture of\u00a0recognition\u00a0for every segment of the workforce.<\/p> <\/div>

        Can AI-powered recognition platforms integrate with an existing HRMS or engagement platform?<\/strong><\/strong>

        Yes. Most AI-powered recognition platforms\u00a0integrate seamlessly with existing HRMS, collaboration and employee engagement platforms<\/a>. By\u00a0leveraging\u00a0employee data and automating workflows, organisations can deliver more\u00a0timely\u00a0and\u00a0personalised recognition\u00a0experiences\u00a0while improving adoption, reducing administrative effort and\u00a0unlocking the ROI of\u00a0employee\u00a0recognition\u00a0programs.\u00a0<\/p> <\/div>

        How do AI-powered R&R programs stay compliant in regulated sectors like BFSI or pharmaceuticals?<\/strong>\u00a0<\/strong>

        AI-powered\u00a0R&R\u00a0platforms\u00a0support compliance in\u00a0regulated sectors\u00a0through\u00a0transparent\u00a0audit trails,\u00a0secure data handling, configurable approval\u00a0workflows\u00a0and\u00a0governance controls.\u00a0With\u00a0the right safeguards in place, organisations in regulated industries can confidently\u00a0design and\u00a0implement AI powered R&R programs while\u00a0ensuring data security,\u00a0accountability\u00a0and compliance.<\/p> <\/div> <\/div>\n<\/div>\n\n\n\n

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        Looking to drive employee engagement with AI-powered recognition<\/strong>?<\/h2>\n\n\n\n
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        Let’s talk <\/a><\/div>\n<\/div>\n<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

        In today’s tech-driven world, AI is transforming everyday experiences and business operations. As it evolves, understanding its psychological impact is key\u2014especially in AI-powered Employee Reward & Recognition (R&R) programs. 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as\u00a0engagement,\u00a0retention,\u00a0productivity\u00a0and\u00a0performance\u00a0\u2013\u00a0not\u00a0just\u00a0the number of recognitions sent or rewards redeemed.\u00a0AI-powered\u00a0R&R\u00a0platforms\u00a0make this easier by surfacing real-time, data-driven insights,\u00a0predictive analytics,\u00a0and actionable recommendations,\u00a0instead of retrospective reporting, turning\u00a0recognition into a\u00a0measurable\u00a0lever for\u00a0business\u00a0performance.\u00a0","inLanguage":"en-US"},"inLanguage":"en-US"},{"@type":"Question","@id":"https:\/\/www.biworldwide.com\/en-in\/our-work\/blog\/the-human-side-of-ai-in-rr-insights-into-behavioral-science-psychology\/#faq-question-1784878270064","position":3,"url":"https:\/\/www.biworldwide.com\/en-in\/our-work\/blog\/the-human-side-of-ai-in-rr-insights-into-behavioral-science-psychology\/#faq-question-1784878270064","name":"Do AI-powered\u00a0recognition\u00a0platforms\u00a0support regional languages, not just English?","answerCount":1,"acceptedAnswer":{"@type":"Answer","text":"Yes.\u00a0New-age AI-powered R&R platforms support multiple regional languages, making recognition more inclusive and meaningful.\u00a0Language is\u00a0often a key barrier\u00a0to\u00a0the adoption of AI-powered R&R programs,\u00a0especially\u00a0among\u00a0regional\u00a0and frontline\u00a0workforces.\u00a0In\u00a0countries like\u00a0India,\u00a0multilingual\u00a0support\u00a0ensures\u00a0recognition reaches every employee,\u00a0as\u00a0recognition delivered only in English can exclude\u00a0a significant portion\u00a0of the workforce it aims to engage.\u00a0This helps\u00a0organisations\u00a0drive engagement across the board and\u00a0maximise the\u00a0ROI of R&R\u00a0programs.\u00a0","inLanguage":"en-US"},"inLanguage":"en-US"},{"@type":"Question","@id":"https:\/\/www.biworldwide.com\/en-in\/our-work\/blog\/the-human-side-of-ai-in-rr-insights-into-behavioral-science-psychology\/#faq-question-1784878281807","position":4,"url":"https:\/\/www.biworldwide.com\/en-in\/our-work\/blog\/the-human-side-of-ai-in-rr-insights-into-behavioral-science-psychology\/#faq-question-1784878281807","name":"Can AI-powered recognition platforms\u00a0adapt to a multigenerational and multicultural workforce?\u00a0\u00a0","answerCount":1,"acceptedAnswer":{"@type":"Answer","text":"Absolutely.\u00a0This is\u00a0often a big barrier for adopting\u00a0AI-powered\u00a0R&R platforms\u00a0in India.\u00a0However,\u00a0such\u00a0platforms\u00a0enable\u00a0personalising\u00a0recognition\u00a0for\u00a0generations,\u00a0roles,\u00a0cultural\u00a0nuances\u00a0and individual preferences\u00a0across a diverse workforce.\u00a0This ensures recognition feels authentic,\u00a0relevant\u00a0and motivating\u00a0for every employee, while helping organisations\u00a0unlock\u00a0the\u00a0ROI of\u00a0R&R\u00a0programs.\u00a0","inLanguage":"en-US"},"inLanguage":"en-US"},{"@type":"Question","@id":"https:\/\/www.biworldwide.com\/en-in\/our-work\/blog\/the-human-side-of-ai-in-rr-insights-into-behavioral-science-psychology\/#faq-question-1784878295850","position":5,"url":"https:\/\/www.biworldwide.com\/en-in\/our-work\/blog\/the-human-side-of-ai-in-rr-insights-into-behavioral-science-psychology\/#faq-question-1784878295850","name":"How do AI-powered recognition programs work for frontline, factory-floor and deskless employees?\u00a0","answerCount":1,"acceptedAnswer":{"@type":"Answer","text":"AI-powered R&R platforms\u00a0are built to\u00a0enable recognition for\u00a0frontline, factory-floor and deskless employees\u00a0through mobile-first, easy-to-access\u00a0experiences that do\u00a0not rely on\u00a0desktop access.\u00a0The platforms\u00a0also\u00a0simplify rewards\u00a0redemption\u00a0for such employees,\u00a0helping organisations create a more inclusive\u00a0culture of\u00a0recognition\u00a0for every segment of the workforce.","inLanguage":"en-US"},"inLanguage":"en-US"},{"@type":"Question","@id":"https:\/\/www.biworldwide.com\/en-in\/our-work\/blog\/the-human-side-of-ai-in-rr-insights-into-behavioral-science-psychology\/#faq-question-1784878320784","position":6,"url":"https:\/\/www.biworldwide.com\/en-in\/our-work\/blog\/the-human-side-of-ai-in-rr-insights-into-behavioral-science-psychology\/#faq-question-1784878320784","name":"Can AI-powered recognition platforms integrate with an existing HRMS or engagement platform?","answerCount":1,"acceptedAnswer":{"@type":"Answer","text":"Yes. Most AI-powered recognition platforms\u00a0integrate seamlessly with existing HRMS, collaboration and <a href=\"https:\/\/www.biworldwide.com\/en-in\/elevate\/\">employee engagement platforms<\/a>. By\u00a0leveraging\u00a0employee data and automating workflows, organisations can deliver more\u00a0timely\u00a0and\u00a0personalised recognition\u00a0experiences\u00a0while improving adoption, reducing administrative effort and\u00a0unlocking the ROI of\u00a0employee\u00a0recognition\u00a0programs.\u00a0","inLanguage":"en-US"},"inLanguage":"en-US"},{"@type":"Question","@id":"https:\/\/www.biworldwide.com\/en-in\/our-work\/blog\/the-human-side-of-ai-in-rr-insights-into-behavioral-science-psychology\/#faq-question-1784878330123","position":7,"url":"https:\/\/www.biworldwide.com\/en-in\/our-work\/blog\/the-human-side-of-ai-in-rr-insights-into-behavioral-science-psychology\/#faq-question-1784878330123","name":"How do AI-powered R&R programs stay compliant in regulated sectors like BFSI or pharmaceuticals?\u00a0","answerCount":1,"acceptedAnswer":{"@type":"Answer","text":"AI-powered\u00a0R&R\u00a0platforms\u00a0support compliance in\u00a0regulated sectors\u00a0through\u00a0transparent\u00a0audit trails,\u00a0secure data handling, configurable approval\u00a0workflows\u00a0and\u00a0governance controls.\u00a0With\u00a0the right safeguards in place, organisations in regulated industries can confidently\u00a0design and\u00a0implement AI powered R&R programs while\u00a0ensuring data security,\u00a0accountability\u00a0and compliance.","inLanguage":"en-US"},"inLanguage":"en-US"}]}},"_links":{"self":[{"href":"https:\/\/www.biworldwide.com\/en-in\/wp-json\/wp\/v2\/posts\/98","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.biworldwide.com\/en-in\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.biworldwide.com\/en-in\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.biworldwide.com\/en-in\/wp-json\/wp\/v2\/users\/21"}],"replies":[{"embeddable":true,"href":"https:\/\/www.biworldwide.com\/en-in\/wp-json\/wp\/v2\/comments?post=98"}],"version-history":[{"count":21,"href":"https:\/\/www.biworldwide.com\/en-in\/wp-json\/wp\/v2\/posts\/98\/revisions"}],"predecessor-version":[{"id":6294,"href":"https:\/\/www.biworldwide.com\/en-in\/wp-json\/wp\/v2\/posts\/98\/revisions\/6294"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.biworldwide.com\/en-in\/wp-json\/wp\/v2\/media\/108"}],"wp:attachment":[{"href":"https:\/\/www.biworldwide.com\/en-in\/wp-json\/wp\/v2\/media?parent=98"}],"wp:term":[{"taxonomy":"content-topic","embeddable":true,"href":"https:\/\/www.biworldwide.com\/en-in\/wp-json\/wp\/v2\/content-topic?post=98"},{"taxonomy":"problem-space","embeddable":true,"href":"https:\/\/www.biworldwide.com\/en-in\/wp-json\/wp\/v2\/problem-space?post=98"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}