05_Mverecha,

Abstract

This paper explores the convergence of Indigenous Knowledge Systems (IKS) and Artificial Intelligence (AI) to address climate change, utilising a qualitative research methodology. It illustrates how AI can assist IKS-centred climate projects, creating opportunities for collaborative creation and knowledge exchange. The results obtained through focus group discussions, in-depth interviews, and direct observation indicate that climate change poses significant challenges for Indigenous communities, which are already dealing with its negative impacts. It emerged from the discussions that IKS offers a crucial understanding of sustainable practices and environmental stewardship, while AI presents creative approaches for both mitigating and adapting to climate change. The research underscores the importance of centring Indigenous knowledge in AI-enhanced climate solutions, demonstrating how the fusion of IKS and AI can lead to more inclusive and impactful responses to climate issues. However, obstacles related to cultural appropriateness and insufficient contextualised data impede AI’s effectiveness in places like Zimbabwe. Consequently, the paper advocates for stakeholders to leverage the strengths of IKS-based initiatives alongside AI advancements to formulate customised strategies for addressing climate change, especially in regions such as Masvingo, which are confronting climate-related difficulties.

Keywords: IKS, AI, integration, climate change, collaborative, sustainable practices

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Introduction

Indigenous Knowledge Systems (IKS), utilised over many generations, include the traditions, practices, and ecological insights of local communities. These systems provide important perspectives on sustainable farming methods, biodiversity preservation, and resource management. For example, farmers in Masvingo historically leveraged their understanding of seasonal trends and local ecosystems to guide their planting times and crop choices [Zvobgo et al., 2023]. This extensive knowledge was crucial in building resilient agricultural methods that naturally acknowledged local conditions and contributed to sustainable land use. Nevertheless, climate change introduced significant challenges that demanded not only local wisdom but also advances in technology to deal effectively with evolving environmental conditions. Artificial Intelligence (AI), owing to its capabilities in data analysis, predictive analytics, and rapid decision-making, has emerged as a formidable resource that can improve agricultural output while fostering sustainability [Sibanda, 2023]. AI technologies play a role in predicting weather changes, maximising resource efficiency, and selecting crops more suitable for altered climatic scenarios. The opportunity to combine AI with agricultural practices presents a pathway to strengthen the resilience of farmers in Masvingo, ultimately addressing the various challenges that climate change brings.

To investigate the integration of IKS and AI for climate adaptation in Masvingo, this study utilised a qualitative research approach. Focus group discussions and detailed interviews provided rich, contextual information, while purposive sampling ensured that the participants had pertinent knowledge and experience regarding both Indigenous methodologies and AI innovations. Thematic analysis revealed notable themes and insights that emerged from the data, offering a thorough understanding of how these two knowledge frameworks could collaboratively enhance farmers’ resilience to climate change. Through this research, the objective was to demonstrate AI’s potential to strengthen IKS-based agricultural practices and ultimately tackle the intricate challenges posed by climate change in the region.

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Background of the Study

This research investigates the connection between Indigenous Knowledge Systems (IKS) and Artificial Intelligence (AI) regarding climate-related decision-making among smallholder farmers in Masvingo, Zimbabwe. With ongoing climate change worsening the unpredictability of seasonal rainfall, agricultural practices in the region have become increasingly vulnerable. As noted by Sibanda et al. [2020] and Zvobgo et al. [2023], there is an urgent demand for smallholder farmers to implement effective adaptation strategies that draw from both traditional knowledge and modern technological insights. The incorporation of climate and weather forecasts into their decision-making is considered essential for improving resilience to climate variability and securing food supply.

Globally, there is a growing acknowledgement of the complementary roles that IKS and AI can serve in tackling climate change issues. The Intergovernmental Panel on Climate Change (IPCC [2022]) emphasises the significance of cooperative approaches that utilise both Indigenous knowledge and scientific progress to guide adaptation strategies. This dual perspective is particularly pertinent for agricultural communities, where local knowledge about ecological changes has traditionally informed sustainable practices. Research conducted in Brazil serves as an example of this combination, showcasing that insights from IKS and AI can yield nuanced understandings of local environmental shifts that often exceed those provided by traditional scientific approaches [El-Hani et al., 2022]. Such results underscore the potential for merging Indigenous knowledge with AI modelling to enhance our grasp of climate dynamics and improve local adaptive measures. The ramifications of merging IKS with AI systems are significant, particularly regarding household-level decision-making on climate adaptation among smallholder farmers. By investigating how these two knowledge systems interact and inform each other, this study deepens our understanding of effective adaptation strategies that are specifically relevant to the distinct challenges encountered by farmers in Masvingo. Ultimately, the research aspires to contribute to the conversation on adaptive capacity amid climate change, illuminating ways to strengthen resilience and sustainability in agricultural methods. The fusion of IKS with AI is not solely a technical pursuit but also a socio-cultural one. It requires recognising the local context and the values inherent in Indigenous knowledge. Scholars argue that for AI to be effectively embraced within communities, it must honour and integrate the cultural aspects of farming practices [Zhou et al., 2022]. Collaborations involving local farmers, agricultural specialists, and technology creators are vital to ensure that AI applications cater to the farming realities experienced by Masvingo farmers. This kind of collaboration can promote the creation of AI tools that utilise Indigenous insights, thereby boosting their relevance and efficacy.

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Community Engagement and Resilience

Empirical studies conducted in Masvingo indicate that farmers are more receptive to technology if it aligns with their traditional practices. Community members express a strong desire for their Indigenous knowledge to be acknowledged and incorporated into contemporary agricultural initiatives. This underscores the necessity for a framework that fosters collaborative learning, melding traditional knowledge with modern technological solutions. Involving farmers in the design and implementation of AI tools can lead to innovations that honour local wisdom while leveraging the transformative potential of technology. Furthermore, the combination of Indigenous Knowledge Systems (IKS) and Artificial Intelligence (AI) can improve community cohesion and resilience. By focusing on shared knowledge and local governance, this strategy reinforces social connections among farmers in Masvingo, helping them confront the challenges brought about by climate change together. Collaborative approaches that incorporate both IKS and AI create an atmosphere where farmers can manage their agricultural practices adaptively in response to climate variability, exchanging knowledge gained from their experiences with insights produced by AI systems. Integration, however, faces several obstacles. Critical considerations related to governance frameworks, resource distribution, and technology access need careful evaluation [Mabhiza and Munyiri, 2023]. It is crucial to guarantee that all farmers, particularly those from marginalised backgrounds, have equal access to AI tools to promote inclusive adaptation and mitigation approaches. Technological solutions must not deepen existing inequalities but should encourage fair results that align with local contexts.

Merging Indigenous Knowledge Systems with Artificial Intelligence offers a promising avenue for improving climate change adaptation and mitigation efforts among farmers in Masvingo, Zimbabwe. By appreciating local knowledge while utilising technological progress, stakeholders can create more effective agricultural strategies that withstand the impacts of climate change. This integrated method demands a dedication to recognising the significance of co-learning, equitable technology access, and local governance, ensuring that interventions are deeply embedded in the cultural and social dynamics of the communities they intend to support. As climate change continues to threaten food security and agricultural sustainability in Zimbabwe, this research highlights the urgent need for innovative approaches that honour and harness the rich knowledge inherent in Indigenous practices.

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Statement of the Problem

The effects of climate change pose significant existential challenges to the livelihoods and cultural identities of Indigenous populations in Zimbabwe. As these communities wrestle with increasingly unpredictable weather patterns and environmental conditions, the vast traditional knowledge they hold remains an underappreciated asset within the broader conversation on climate change. Indigenous Knowledge Systems (IKS) are often overlooked despite their richness, depth, and complexity, as smallholder farmers face serious environmental shifts. These systems, deeply rooted in generational experience and close ties to local ecosystems, are crucial for sustainable agricultural practices and environmental management [Mabhiza, 2023]. Even though this traditional knowledge is valuable, Indigenous communities are often sidelined in national and international climate change policy dialogues. These discussions typically prioritise scientific viewpoints and external interests, which results in Indigenous perspectives being overlooked and their contributions undervalued. This exclusion raises important issues regarding the regard for knowledge and the representation of diverse communities in shaping climate adaptation and mitigation strategies. The prevailing narratives dominating climate discussions frequently neglect the lived experiences and innovative solutions proposed by Indigenous peoples that could significantly help in addressing climate challenges. Concurrently, the rapidly growing field of Artificial Intelligence (AI) presents new, data-driven approaches to various global issues, including climate change. The swift advancements in AI technology generate optimism regarding their potential use in tackling environmental problems. However, as AI solutions are implemented, they often lack adequate consideration of local contexts and the socio-ecological dynamics specific to Indigenous communities. This oversight can lead to interventions that are not only ineffective but also risk worsening existing vulnerabilities. The disconnect between technology-driven approaches and the nuanced realities of local environments highlights a crucial epistemological conflict between traditional knowledge and scientific methods. In this context, the present research explores the philosophical foundations of merging Indigenous Knowledge Systems with Artificial Intelligence.

The objective is to create climate change adaptation and mitigation strategies that are not just cognizant of cultural sensitivities but also genuinely effective within the Zimbabwean context. By examining the power dynamics present in the conversation around climate change policy, this study intends to rectify the existing biases that typically advantage scientific paradigms. The research emphasises the vital necessity of fairly acknowledging Indigenous insights and their potential to shape modern climate action. The envisioned integration of IKS with AI is seen as a means to deliver substantial advantages for Indigenous communities, encouraging more holistic and inclusive methods for adapting to climate change [Zhou et al., 2024]. This integration goes beyond simple technical collaboration; it symbolises a philosophical dedication to acknowledging, honouring, and valuing various forms of knowledge. By linking traditional wisdom with the innovative potential of AI, the research aspires to uncover strategies that boost climate resilience while reshaping developmental frameworks. Ultimately, this investigation seeks to empower local communities by enabling them to regain control over their adaptation and mitigation strategies. The study suggests that when Indigenous knowledge and technological advancement work together, they can promote sustainable practices that not only address climate change effectively but also safeguard and sustain cultural identities. In this way, the research enhances the understanding of how diverse knowledge systems can come together to tackle the severe challenges posed by climate change, fostering justice, equity, and resilience in affected communities.

The importance of this research lies in its comprehensive strategy to create climate change solutions that are specifically adapted to the distinct socio-cultural and environmental settings of Zimbabwe, thereby promoting sustainable development and equity in climate action. At a time when climate change is among the most urgent global issues, there is an essential need for strategies that resonate with local experiences and the traditional wisdom of communities. This study highlights the crucial necessity of recognising and amplifying Indigenous Knowledge Systems (IKS) in the formulation of climate change policies. By integrating IKS into the conversation surrounding climate issues, decision-makers can tap into centuries of knowledge about environmental care, resource management, and effective adaptation strategies that have been successful across various ecological landscapes.

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IKS and AI Integration Socio-Cultural Effects

A further important significance of this research is the investigation of the cultural and social ramifications of incorporating Artificial Intelligence (AI) within Indigenous communities. While AI has the potential to greatly improve climate resilience through data analysis and predictive modelling, its application should be handled with care and cultural awareness [Mawere, 2024]. This research emphasises the necessity of grasping how AI technologies might affect local practices, social frameworks, and cultural identities. Involving Indigenous communities in conversations about the deployment of AI can reveal concerns surrounding data ownership, representation, and ethical implications. Additionally, by analysing these impacts, policymakers and developers can create AI solutions that not only tackle environmental challenges but also resonate with the values and goals of Indigenous populations, fostering a sense of ownership and empowerment over technological advancements. This research calls for the acknowledgement of IKS as a critical element in developing climate change policies. Traditional ecological knowledge consists of the observations, practices, and beliefs that have developed within communities over generations, often specifically suited to the region’s climatic and ecological circumstances. By promoting IKS within policy discussions, this study highlights a two-way learning framework where scientific knowledge and Indigenous wisdom can converge to formulate more effective, practical, and culturally attuned climate strategies. This approach not only respects the existing knowledge of Indigenous communities but also empowers them, ensuring their perspectives are prioritised in discussions that shape their futures.

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Context-Sensitivity and Inclusive Climate Change Responses

The third noteworthy aspect of this research focuses on the importance of climate change responses that are sensitive to context, participatory, and inclusive. As climate change presents itself differently across various regions, including Zimbabwe, it is vital to develop tailored responses that take into account local circumstances, customs, and community dynamics. This study supports methodologies that encourage active involvement from Indigenous communities in identifying, planning, and executing climate strategies. Such participatory frameworks can enhance community engagement, ensure that initiatives reflect local priorities, and build greater resilience to the impacts of climate change. By advocating for inclusivity in climate action, this research aims to disrupt traditional power dynamics by fostering dialogue among policymakers, scientists, and Indigenous knowledge holders. This inclusive approach acknowledges that different knowledge systems can uniquely contribute to comprehending and addressing the complexities of climate issues. Ultimately, enhancing collaboration among diverse stakeholders enriches the effectiveness of climate responses, paving the way for sustainable development that honours both environmental integrity and social justice.

Overall, the significance of this research extends beyond conventional environmental studies to encompass critical themes of justice, agency, and cultural respect. By advocating for the integration of Indigenous Knowledge Systems into climate change policymaking, exploring the impacts of AI within Indigenous contexts, and emphasising the need for participatory and context-sensitive responses, this study lays the groundwork for innovative and effective solutions tailored to Zimbabwe’s unique challenges. As the global community grapples with the realities of climate change, such approaches become essential not only in promoting resilience within affected ecosystems but also in upholding the dignity and rights of those who call these communities home [Mugambiwa, 2020]. The findings of this research contribute to the broader discourse on sustainable development and climate equity, highlighting the invaluable role that local knowledge and cultural heritage play in shaping a more equitable and sustainable future.

Related Literature

The merging of Indigenous Knowledge Systems (IKS) with Artificial Intelligence (AI) has emerged as a burgeoning area of research in climate adaptation and mitigation. Researchers from various regions and backgrounds have investigated the potential benefits of combining these two knowledge frameworks, emphasising how their synergy can enhance resilience in response to climate change. This literature review begins with broader international discussions and gradually narrows its focus to relevant studies and applications within Zimbabwe.

International Perspectives

Worldwide, many scholars have acknowledged the significance of IKS as a vital resource in climate science. For instance, Berkes [2019] stresses the value of Indigenous knowledge in comprehending ecosystem dynamics, asserting that it provides detailed insights that can complement scientific data. He supports a collaborative approach that fuses local wisdom with scientific methods to tackle complex adaptive systems such as climate change. This intersection is further supported by Davis and Ransom [2020], who investigate how IKS can contribute to ecological modelling and management strategies within biodiversity conservation. AI technologies present the opportunity to boost climate adaptation efforts by analysing large volumes of data for predictive modelling. A study by Liu et al. [2019] illustrated how AI-driven algorithms could recognise patterns in environmental data, aiding in the forecasting of climate-related events. Nonetheless, they warn that failing to incorporate local knowledge into AI applications may inadvertently neglect essential socio-ecological contexts, potentially undermining their effectiveness. This highlights the need for a hybrid model that acknowledges and integrates IKS within AI-based solutions. Moreover, the combination of IKS and AI is not without its hurdles. As noted by Ndlovu-Gatsheni [2018], the dominance of Western scientific methodologies often overlooks the foundational epistemologies of Indigenous practices, thus perpetuating power inequalities. Establishing equitable partnerships in knowledge co-production is essential for addressing historical injustices and fostering authentic collaboration.

Regional Insights in Africa

In Africa, researchers are increasingly recognising the importance of merging IKS with AI for climate action. For instance, Bhandari et al. [2021] examined the use of AI in water management and agricultural practices across various African countries, highlighting the significance of community-based knowledge. Their findings indicate that AI can improve resource management when developed to align with Indigenous practices. They advocate for the establishment of participatory frameworks that prioritise local voices in the technological development process. The contribution of IKS in enhancing community resilience against climate change has also been documented by Mooney and Hendershot [2019], who studied the strategies utilised by Indigenous communities in East Africa to address drought and food insecurity. Their research emphasises the effectiveness of traditional methods in achieving sustainable outcomes, particularly in scenarios where technological solutions may be limited or unsuitable. The integration of AI could support these initiatives by providing additional predictive insights while preserving the autonomy of Indigenous communities.

Specific Studies in Zimbabwe

Shifting attention to Zimbabwe, the combination of Indigenous Knowledge Systems (IKS) and Artificial Intelligence (AI) is becoming recognised as an effective method to tackle climate challenges. Researchers like Chikozho et al. [2017] have explored the potential of IKS to shape climate policies in Zimbabwe, advocating for collaborative approaches that merge local knowledge with contemporary scientific methods. They highlight that communities in Zimbabwe hold substantial traditional knowledge related to agricultural practices, which can be enhanced through the application of AI technologies to improve climate adaptation strategies. A significant illustration in Zimbabwe is the research conducted by Mavoko and Tchervenkov [2020], who analysed the use of AI in optimising water management and crop selection in rural settings. Their findings indicated that local farmers appreciated traditional knowledge but encountered difficulties in adopting modern agricultural techniques, particularly concerning the interpretation of climate forecasts produced by AI. They recommend developing platforms that integrate local practices with AI-generated insights to enable knowledge sharing and the effective execution of agricultural strategies.

Additionally, the incorporation of IKS into AI systems extends beyond agriculture in Zimbabwe. Researchers such as Ndaba and Mabhena [2021] have investigated how Indigenous viewpoints can influence disaster risk reduction methods concerning climate-induced hazards. They argue that Indigenous communities often possess profound knowledge about local environmental conditions and natural disasters, which can significantly enhance the effectiveness of AI-driven early warning systems when integrated properly. In conclusion, the review of the literature suggests that combining Indigenous Knowledge Systems with Artificial Intelligence has notable potential for climate adaptation and mitigation, from global frameworks to localised initiatives in Zimbabwe. The discussions increasingly highlight the necessity for hybrid models that meld IKS and AI, drawing insights from international perspectives that stress collaborative methods as well as African studies that recognise the distinct challenges and benefits of local knowledge.

As research continues to progress, it underscores the need for participatory strategies that prioritise Indigenous perspectives, ensuring that technological advancements remain relevant to the context and culturally suitable. The fusion of these knowledge systems not only strengthens resilience but also advances climate justice, ultimately leading toward a future that is more sustainable and equitable. In Zimbabwe, this integration is especially crucial as communities work to adapt to climate challenges while maintaining their rich cultural heritage and ecological knowledge.

Methodology

The study adopted a qualitative approach to investigate the fusion of Indigenous Knowledge Systems (IKS) with Artificial Intelligence (AI) to tackle climate change issues in Masvingo, Zimbabwe. This choice is based on the ability of qualitative methods to capture detailed and nuanced insights into participant experiences, viewpoints, and cultural backgrounds [Creswell, 2013]. Qualitative techniques allow for the exploration of complex social phenomena, making them especially suited for analysing the relationship between traditional knowledge and contemporary technological solutions. The research utilised purposive sampling to select participants with substantial knowledge and experience relevant to the research themes. Participants were chosen according to specific criteria, such as their participation in community-driven climate action efforts, expertise in traditional practices, and willingness to discuss the impact of AI in these areas [Patton, 2015]. This deliberate selection approach ensured that the information collected was pertinent and valuable, enhancing the understanding of the community’s viewpoints. Regarding data collection methods, in-depth interviews served as a primary data collection method, enabling thorough conversations about participants’ experiences with IKS, their perceptions of AI, and their thoughts on climate change. The semi-structured format of the interviews allowed for flexibility, enabling participants to convey thoughts that might not have been anticipated while also covering essential topics [Kvale and Brinkmann, 2015]. Interviews were conducted in the native languages of participants when possible, fostering comfort and encouraging meaningful dialogues.

In addition to in-depth interviews, focus group discussions allowed for a collective examination of shared experiences and community knowledge, promoting dialogue about the merger of IKS and AI. This methodology utilised group dynamics to expand upon ideas shared in individual interviews and provided a platform for participants to build upon each other’s insights [Krueger and Casey, 2015]. The focus groups aimed to include a diverse range of voices, encompassing elders, community leaders, youth, and women. Participant observation was also used to immerse researchers in the everyday lives of community members. By directly engaging with their activities, such as traditional agricultural practices, community meetings, and nature-related rituals, researchers developed a deeper understanding of how IKS shapes environmental stewardship. This approach enables researchers to observe contextual elements, social interactions, and cultural practices that influence the experience and management of climate change [Spradley, 2016].

The ethnographic method combines the previously mentioned approaches, highlighting the importance of holistic engagement with the community. The active participation and observation of the research team in natural settings shed light on the intricacies and connections between cultural and technological factors impacting climate change responses. Ethnographic techniques are particularly effective for comprehending the lived experiences of communities, especially in studies focused on Indigenous viewpoints [Clifford and Marcus, 1986]. Within the ethnographic framework, specific case studies were selected based on two criteria: communities with extensive IKS and those showing potential openness to AI applications. This focused strategy ensured that the research findings would not only contribute to academic discussions but also improve understanding within practical settings and guide future collaborative efforts [Yin, 2018].

A unique element of this study was the focus on collaborative research. Involving Indigenous communities in the co-development of AI solutions fosters the joint creation of knowledge that honours and integrates their IKS while introducing technological benefits. Collaborative research aligns with participatory action research principles, which advocate that those impacted by issues should play a significant role in developing solutions [Reason and Bradbury, 2008]. By actively engaging community members in the research process, the study aimed to empower these communities, promoting ownership of both the knowledge and the results while enhancing the relevance and applicability of AI technologies within their socio-cultural landscape.

Basically, the selected qualitative approach, which employs purposive sampling along with a range of data collection techniques such as in-depth interviews, focus group discussions, and participant observation, establishes a strong foundation for investigating the incorporation of Indigenous Knowledge Systems and Artificial Intelligence in tackling climate change in Masvingo, Zimbabwe. By prioritising collaboration and community involvement, this approach enhances the understanding of how traditional knowledge and technological innovation interact, thereby supporting sustainable development initiatives in the area.

Results and Analysis

The urgency of climate change necessitates innovative approaches that reconcile traditional and contemporary knowledge frameworks. This exploration draws upon Indigenous Knowledge Systems (IKS) and Artificial Intelligence (AI) within the context of Masvingo, Zimbabwe. It intertwines philosophical inquiries, including epistemological, ontological, and ethical implications, while employing post-colonial theories to critique the existing power structures that shape knowledge production and environmental engagement.

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Themes Emerging from the Research

Epistemological Conflicts and Synergies

The combination of Indigenous Knowledge Systems (IKS) and Artificial Intelligence (AI) blurs the line between age-old wisdom and empirical research. IKS, which is frequently regarded as merely anecdotal in mainstream scientific conversations, consists of well-established ecological knowledge passed down through generations. For instance, communities in Masvingo employ traditional methods for managing resources and promoting sustainability. One village Chief said:

“Isu chatinoda muno mudunhu medu, hunhu, zvino hatizivi kuti chirungu chomoda kutipa ichi, chamunoti ndeche ma computer, zvinodyidzana here netsika dzeku. Kana zvichidyidzana zvakanaka tinogamuchira, asi aiwa hatitange nekugashira chirumbi ichi tisati tabvunzawo masvikiro edu. (We appreciate what we have in our community, which is our culture. We are unsure about what the computer can offer us. Does it connect with our traditions? If it integrates well, we welcome it. However, we will not readily accept this new technology without first consulting our ancestors.”

On the other hand, AI provides a structured and data-oriented approach to addressing climate change and developing policies. This study discovered that while IKS offers valuable, context-specific perspectives regarding local ecosystems, AI boosts predictive capabilities and scalability. Nevertheless, as scholars like Agrawal [2002] and Tuhiwai Smith [2012] have noted, this integration must honour and recognise Indigenous knowledge systems instead of overshadowing them with Western ideologies. The conversation must remain mindful of how knowledge is perceived and valued, promoting a collaborative learning framework in which both forms of expertise enhance the dialogue surrounding climate change.

Ontological Perspectives: Nature and the Divine

From a religious standpoint, the intertwining of IKS and AI raises significant inquiries about the essence of creation and humanity’s place within it. Indigenous understanding emphasises a relational perspective on existence, nurturing a sense of responsibility towards the Earth, which resonates with numerous religious beliefs. One respondent noted that:

“Tagara isu tine nzira dzedu dzatinoshandisa kukumbira nadzo mvura yakanaka isina njodzi, dzakaita semnheni. Uye tinogara tatozi nechekare kupfurikidza nemasvikiro edu atinoti manyusa kana kuti vanaisi vemvura. Vanototi udza kana kuchiuya dutu remvura ine mhirizhonga, tinotoziviswa uye toudzwa kuti tokumbirira sei kuti tipone. (We already possess methods for requesting safe and favourable rain, such as observing nature. Our ancestors would typically forewarn us about potential storms and guide us on how to proceed to ensure our safety.)”

This sentiment indicates that we already have our practices for invoking rain that avoids risky thunderstorms. Our ancestors would alert us about dangers ahead of time and guide how to navigate them. In exploring this dimension, we draw upon eco-theological writings (e.g., McFague [2013]) that promote a worldview of interconnectedness, pointing out that climate change harms God’s creation. The inclusion of AI in environmental stewardship represents a transition toward mechanistic views unless it is utilised with a framework of care and accountability. The findings indicate that integrating ethical considerations into scientific advancement can promote a more comprehensive strategy for climate resilience, harmonising technological progress with spiritual and cultural narratives.

Ethical Dimensions of Technological Integration

The ethical aspects concerning the fusion of IKS and AI are essential, as the research highlighted issues related to data sovereignty, representation, and fairness. Post-colonial theorists like Spivak [1988] stress the importance of not marginalising Indigenous voices in techno-scientific initiatives. Involving communities in the data-gathering process cultivates a sense of ownership and honours local knowledge. Additionally, ethical frameworks rooted in IKS champion sustainability and justice, contesting the exploitative practices often associated with technology in underprivileged communities. The study indicates that the development of ethical AI must incorporate Indigenous values such as kinship with the land and reciprocity with nature, suggesting avenues for a more inclusive approach to climate solutions. One respondent noted that “dambudziko ratinaro kuti tisada kugashira chirungu ichi ndeche ma computers, nderekuti isu patsika dzedu hatizooni zvine unhu, uye isu tinoda kuchengeta tsika dzedu dzechivanhu.” To express it differently, our challenge with blending IKS and AI lies in our desire to uphold our IKS values of hunhu, and we do not wish for AI innovations and solutions to overshadow our IKS.

Socio-Political and Cultural Contexts

Understanding the socio-political environment is crucial to grasping how IKS and AI can work together for climate resilience. The ethnographic insights reveal that traditional practices function within power dynamics shaped by colonial legacies and current governance systems. Participants express a wish for independence in managing their resources, echoing Lumumba’s [2014] concept of epistemic justice, where Indigenous viewpoints reclaim authority in environmental dialogues. The research underscores the possibility for AI technologies to either strengthen or undermine these power dynamics. When integrated effectively, AI can empower communities in Masvingo to tackle climate effects, thereby fostering localised solutions that align with cultural identity and values. Conversely, imposing technology from the top down risks alienating communities, resonating with the critiques of technological colonialism raised by scholars like Ndlovu-Gatsheni [2018].

Integrating Indigenous Knowledge Systems with Artificial Intelligence

The growing effects of climate change pose extraordinary challenges, particularly in vulnerable areas like Masvingo Province in Zimbabwe. To confront these challenges, innovative solutions that combine different knowledge systems are necessary. This essay explores the merger of Indigenous Knowledge Systems (IKS) with Artificial Intelligence (AI) for climate change mitigation and adaptation, focusing on theological views regarding stewardship, fairness, and human dignity while also addressing the intricacies and prospects presented by these two distinct epistemological approaches.

Knowledge Diversity: Foundations of Epistemology

The convergence of Indigenous Knowledge Systems (IKS) and Artificial Intelligence (AI) showcases a complex array of knowledge distinguished by varied epistemological roots. IKS is founded on the lived experiences and insights of local populations, cultivated over generations through close relationships with their surroundings. Researchers like Agrawal [2002] and Dell’Angelo et al. [2017] assert that IKS encompasses comprehensive views of ecological dynamics, values, and cultural identities. In contrast, AI relies on quantitative analysis, computational models, and data-centric decision-making, often emphasising efficiency at the expense of contextual comprehension. The task of merging these diverse knowledge frameworks is considerable. As highlighted by Tuhiwai Smith [2012], the dominance of Western scientific frameworks can eclipse Indigenous perspectives, risking cultural loss and misrepresentation.

However, a shared framework can emerge from the intertwining of both knowledge systems, prioritizing local experiences while harnessing AI’s analytical capabilities. By promoting an inclusive dialogue around epistemology, we can develop more impactful climate strategies that align with the cultural essence of Masvingo communities.

Contextual Understanding: Experiences versus Computational Views

Indigenous Knowledge Systems are fundamentally context-specific, originating from centuries of engagement with their environment. They provide crucial insights into sustainable practices, including traditional agricultural methods, water conservation strategies, and biodiversity management tailored to the distinct ecological circumstances of Masvingo. This localised wisdom is essential for comprehending how communities manage the climatic challenges they encounter. In contrast, AI offers wider, abstract models for examining climate trends and forecasting future conditions. While this computational methodology can yield valuable predictive data, it might fail to capture the intricacies of local socio-ecological systems essential for effective adaptation. Scholars such as Kearney [2018] warn that an exclusive focus on abstract models can result in uniform solutions that neglect the unique needs and values of communities. Consequently, the merging of IKS and AI necessitates a continuous dialogue in which AI technologies are persistently refined through the lens of Indigenous knowledge. Platforms that enable collaborations between local practitioners and AI developers can facilitate the co-creation of tools that both inform and resonate with community values and practices.

The combination of IKS and AI entails significant ontological implications for how we perceive reality and our connection to the natural environment. IKS promotes a viewpoint of interrelatedness and reciprocity among all beings, advocating for a moral ecological ethic [Meyer, 2021]. This perspective suggests that climate change is not solely a technical or policy concern but is fundamentally a moral and ethical issue rooted in humanity’s connection with creation. Conversely, AI generally emphasises efficiency and optimisation, frequently abstracting human-nature interactions to enhance predictability and control. This mechanistic perspective can obscure the values of stewardship and interconnectedness inherent in IKS. Consequently, questions arise regarding how AI technologies might influence our understanding of reality: Do they promote greater comprehension and responsibility, or do they reduce individuals and communities to mere data points within a broader computational framework? There is a tension between preserving human agency and autonomy in decision-making while employing AI tools. Scholars such as Haraway [2016] argue that technologies should be developed in ways that enhance human agency, especially in critical areas like climate change. Integrating IKS into AI development can help rehumanize technology and ensure alignment with the values of those most impacted by climate-related effects.

Stewardship, Equity and Human Dignity

The theological foundations for merging Indigenous Knowledge Systems (IKS) with Artificial Intelligence (AI) underscore responsibility for creation, respect for human dignity, and fairness. Both Indigenous cultures and numerous theological traditions promote a caring and mutually beneficial relationship with nature. This viewpoint aligns with the increasing recognition that effective climate change strategies must be built on ethical principles that prioritise justice and equity. As noted by researchers like West et al. [2018], approaches that inclusively acknowledge the perspectives of marginalised groups are vital for attaining sustainable outcomes. Furthermore, integrating IKS with AI has the potential to empower communities in Masvingo, allowing them to have a more significant voice and agency in climate-related decision-making. By ensuring that these communities act as co-creators of knowledge and solutions rather than mere subjects of research, we can promote a fairer distribution of power and resources. Integrating IKS and AI may lead to a more sustainable and equitable future, embodying our collective duty as caretakers of creation. Where faith, culture, and technology intersect lies the potential for significant change, promoting local stewardship of the natural environment. Given the intensifying environmental challenges, reassessing our relationship with nature through the lens of Indigenous wisdom paired with advanced technology could reveal transformative solutions for climate resilience and adaptation. Moving forward demands collective effort, encouraging harmony between these distinct knowledge systems in our pursuit of sustainable development and environmental justice.

The insights indicate that combining Indigenous Knowledge Systems (IKS) with Artificial Intelligence (AI) for climate change mitigation and adaptation in Masvingo, Zimbabwe, offers a transformative opportunity to tackle intricate environmental issues. By recognising and honouring the philosophical, epistemological, and ethical components of both systems, we can develop solutions that are not just scientifically sound but also culturally relevant and ethically solid. As we confront the urgent challenges posed by climate change, an inclusive approach that values diverse knowledge and fosters collaborative efforts can lead to the creation of innovative, localised, and effective strategies.

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Conclusion

The urgent threats posed by climate change are particularly pronounced in regions like Africa, where communities contend with increasingly erratic weather, elevated temperatures, and ecological decline. This study has demonstrated that the combination of Indigenous Knowledge Systems (IKS) and Artificial Intelligence (AI) holds considerable promise for tackling these issues through innovative mitigation and adaptation approaches. By acknowledging the distinct strengths of each knowledge system, we have the potential to create collaborative solutions that promote sustainable development while ensuring climate justice.

From a sociological standpoint, this integration transcends a simple blend of knowledge types; it represents a profound acknowledgement of the insights local wisdom provides in addressing climate challenges. IKS is deeply embedded in the cultural, historical, and environmental contexts of communities, offering perspectives on traditional practices that have preserved ecosystems for generations. Conversely, AI delivers analytical thoroughness, scalability, and predictive capabilities, empowering policymakers with data-driven insights that enhance strategy development and execution. The interaction between these forms of knowledge paves the way for culturally relevant solutions that address local contexts while leveraging the technological advancements that shape our contemporary world.

From a philosophical standpoint, the combination of Indigenous Knowledge Systems (IKS) and Artificial Intelligence (AI) challenges the prevailing narratives surrounding knowledge creation and the power dynamics that frequently overlook Indigenous perspectives. It drives us to reconsider our engagement with technology not merely as devices that isolate us from the natural world, but as tools that, when utilised with care and respect, can improve our role as caretakers of the planet. Within this framework, climate justice transcends being solely an environmental issue; it also becomes a social and ethical obligation, promoting fairness and inclusiveness amidst the challenges posed by climate change. This perspective highlights the interconnectedness of all beings and resonates with Indigenous philosophies that promote a balanced coexistence of humans and nature.

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